Search Images Maps Play YouTube News Gmail Drive More »
Sign in
Screen reader users: click this link for accessible mode. Accessible mode has the same essential features but works better with your reader.

Patents

  1. Advanced Patent Search
Publication numberUSRE42473 E1
Publication typeGrant
Application numberUS 11/847,894
Publication dateJun 21, 2011
Filing dateAug 30, 2007
Priority dateMay 30, 2001
Fee statusPaid
Also published asDE60235460D1, EP1393544A1, EP1393544B1, US6937365, US20020181023, WO2002098126A1
Publication number11847894, 847894, US RE42473 E1, US RE42473E1, US-E1-RE42473, USRE42473 E1, USRE42473E1
InventorsIzrail S. Gorian, Jay E. Thornton, Richard A. Pineau
Original AssigneeSenshin Capital, Llc
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Rendering images utilizing adaptive error diffusion
US RE42473 E1
Abstract
An adaptive halftoning method where the difference between a digital image and a filtered digital image is introduced into the system on a pixel by pixel basis is disclosed. In this method, each input difference pixel has a corresponding error value of the previous pixel added to the input value at a summing node, resulting in modified image difference data; the modified image difference data is passed to a threshold comparator where the modified image difference data is compared to a threshold value, the threshold value varying according to the properties of the digital image, to determine the appropriate output level; the output level is subtracted from the modified image difference value to produce the input to an error filter; the output of the error filter is multiplied by an adaptation coefficient, where the adaptation coefficient varies according to the properties of the digital image, to generate the error level for the subsequent input pixel; and, the cyclical processing of pixels is continued until the end of the input data is reached.
Images(6)
Previous page
Next page
Claims(35)
1. A method of generating a halftone image from an input digital image, said input digital image represented by a multiplicity of pixels, each pixel having a given value, said values being stored in a memory, said method comprising the steps of:
(A) determining theone or more properties including local properties of the input digital image;
(B) filtering the input digital image, said filtering having as output a filtered value at each pixel;
(C) obtaining the difference between the value at thea pixel and the filtered value at the pixel, said difference being a threshold input;
(D) generating thean output state for the pixel depending upon the relationship of the value of said threshold input relative to a threshold;
(E) producing an error value, said error value being indicative of the deviation of said threshold input from the output state;
(F) multiplying said error value by a coefficient, the result of said multiplication being stored;
(G) combining the stored value with the difference between the next pixel value and the next filtered value to produce a new threshold input;
(H) repeating steps (D) through (G)the generating an output state, the producing an error value, the multiplying said error value, and the combining the stored error value for each pixel in the input digital image thereby producing a halftone image; and
varying the threshold according to the one or more properties of the input digital image; and
selectively changing the coefficient in step (E) according to the localone or more properties of the input digital image.
2. The method of claim 1 further comprising the step of:
performing a histogram modification of the image pixels, before step (B)filtering the input digital image.
3. The method of claim 1 further comprising the step of:
performing a histogram modification of the difference between the value at the pixel and the filtered value at the pixel, before step (D)generating the output state.
4. The method of claim 1 wherein the selectively changing of the coefficient comprises:
dividing a first function of the localpixel values of the input digital image by a second function of the localpixel values of the input digital image; and
multiplying the absolute value of the result of said division by a first parameter; and
adding a second parameter to the result of the multiplication, thereby obtaining the coefficient.
5. The method of claim 4 wherein said first function is the difference between the value at the pixel and the filtered value at the pixel and said second function is the filtered value at the pixel.
6. The method of claim 4 wherein the threshold is a third function of the localpixel values of the input digital image.
7. The method of claim 6 wherein said third function is a linear function of the localpixel values of the input digital image.
8. The method of claim 6 wherein said third function is a linear function of the local values of the digital image.
9. The method of claim 4 wherein the threshold is the filtered value at the pixel multiplied by a third parameter.
10. The method of claim 9 wherein the filter in step (B) isfiltering comprises using a filter of finite extent, the extent of the filter, the first parameter, the second parametersparameter and the third parametersparameter being selected to produce thean image of highest perceptual quality at a specific output device.
11. The method of claim 9 further comprising the step of:
performing a histogram modification of the difference between the value at the pixel and the filtered value at the pixel, before step (D)generating the output state.
12. The method of claim 1 wherein the input digital image is a monochrome image.
13. The method of claim 1 wherein the input digital image is a color image.
14. A system for generating a halftone image from an input digital image, said input digital image represented by a multiplicity of pixels, each pixel having a given value, said values being stored in a memory, said apparatussystem comprising:
means for determining theone or more properties including local properties of said input digital image; and
means for retrieving the pixel values; and
means for filtering the input digital image, said filtering having as output a filtered value at each pixel; and
means for obtaining the difference between the value at thea pixel and the filtered value at the pixel, said difference being a threshold input; and
means for producing an error value, said error value being indicative of the deviation of said threshold input from thean output state; and
means for multiplying said error value by an adaptation coefficient to obtain a diffused value and
means for storing the diffused value and delaying said stored diffused value by one pixel; and
means for combining the stored delayed diffused value with the difference between the pixel value and the filtered value; and
means for varying thea threshold according to the one or more properties of the input digital image at the pixel value; and
means for selectively changing the adaptation coefficient according to the localone or more properties of the input digital image.
15. The system of claim 14 further comprising:
means performing a histogram modification of the image pixels.
16. The system of claim 14 further comprising:
means for performing a histogram modification of the difference between the value at the pixel and the filtered value at the pixel.
17. The system of claim 14 wherein the means for selectively changing of the adaptation coefficient comprise:
means for dividing a first function of the localpixel values of the input digital image by a second function of the localpixel values of the input digital image; and
means for multiplying the absolute value of the result of said division by a first parameter; and
adding a second parameter to the result of the multiplication, thereby obtaining the adaptation coefficient.
18. A computer program product comprising:
a computer usable storage medium having computer readable code embodied therein for generating a halftone image from an input digital image, said input digital image represented by a multiplicity of pixels, each pixel having a given value, said values being stored in a memory, said code causingcomprising instructions for a computer system to:, the instructions comprising:
instructions to determine theone or more properties including local properties of said input digital image; and
instructions to retrieve the pixel values; and
instructions to filter the input digital image, said filtering having as output a filtered value at each pixel; and
instructions to obtain the difference between the value at thea pixel and the filtered value at the pixel, said difference being a threshold input; and
instructions to produce an error value, said error value being indicative of the deviation of said threshold input from thean output state; and
instructions to multiply said error value by an adaptation coefficient to obtain a diffused value; and
instructions to store the diffused value and delayingdelay said stored diffused value by one pixel; and
instructions to combine the stored delayed diffused value with the difference between the pixel value and the filtered value; and
instructions to vary thea threshold according to the one or more properties of the input digital image at the pixel value; and
instructions to selectively change the adaptation coefficient according to the localone or more properties of the input digital image.
19. The computer program product of claim 18where, the computer readable code further causes the computer system towherein the instructions further comprise:
instructions to perform a histogram modification of the image pixels.
20. The computer program product of claim 18where, the computer readable code further causes the computer system towherein the instructions further comprise:
instructions to perform a histogram modification of the difference between the value at the pixel and the filtered value at the pixel.
21. The computer program product of claim 18where, the computer readable code in causing the computer systemwherein the instructions to selectively change the adaptation coefficient, further causes the computer system tocomprise:
instructions to divide a first function of the localpixel values of the input digital image by a second function of the localpixel values of the input digital image; and
instructions to multiply the absolute value of the result of said division by a first parameter; and
instructions to add a second parameter to the result of the multiplication, thereby obtaining the adaptation coefficient.
22. The computer program product of claim 21 wherein said first function is the difference between the value at the pixel and the filtered value at the pixel and said second function is the filtered value at the pixel.
23. The computer program product of claim 22 wherein said the threshold is the filtered value at the pixel multiplied by a third parameter.
24. The computer program product of claim 23 wherein the filter used to filter the input digital image is a filter of finite extent, the extent of the filter, the first parameter, the second parametersparameter and third parametersparameter being selected to produce thean image of highest quality at a specific output device.
25. The computer program product of claim 25 where, the computer readable code further causes the computer system to18 wherein the instructions further comprise:
instructions to perform a histogram modification of the difference between the value at the pixel and the filtered value at the pixel.
26. The computer program product of claim 21 wherein the threshold is a third function of the localpixel values of the input digital image.
27. The computer program product of claim 26 wherein said third function is a linear function of the localpixel values of the input digital image.
28. The computer program product of claim 26 wherein said third function is a linear function of the local values of the digital image.
29. The computer program product of claim 18 wherein the input digital image is a color image.
30. The computer program product of claim 18 wherein the input digital image is a monochrome image.
31. The system of claim 14, further comprising: a rendering device.
32. The system of claim 31, wherein said rendering device is a binary output device.
33. The system of claim 31, wherein said rendering device is a M-ary display or a M-ary rendering device.
34. The system of claim 31, wherein said rendering device is a mobile phone display.
35. A mobile device capable of generating a halftone image from an input digital image, said input digital image represented by a multiplicity of pixels, each pixel having a given value, said mobile device comprising:
means for determining one or more properties of said input digital image;
means for retrieving the pixel values;
means for filtering the input digital image, said filtering having as output a filtered value at each pixel;
means for obtaining the difference between the value at a pixel and the filtered value at the pixel, said difference being a threshold input;
means for producing an error value, said error value being indicative of the deviation of said threshold input from an output state;
means for multiplying said error value by an adaptation coefficient to obtain a diffused value and means for storing the diffused value and delaying said stored diffused value by one pixel;
means for combining the stored delayed diffused value with the difference between the pixel value and the filtered value;
means for varying a threshold according to the one or more properties of the input digital image at the pixel value;
means for selectively changing the adaptation coefficient according to the one or more properties of the input digital image; and
a rendering device.
Description
BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to the rendering of digital image data, and in particular, to the binary or multilevel representation of images for printing or display purposes

2. Background Description

Since images constitute an effective means of communicating information, displaying images should be as convenient as displaying text. However, many display devices, such as laser and ink jet printers, print only in a binary fashion. Furthermore, some image format standards only allow binary images. For example, the WAP1.1 (Wireless Application Protocol) protocol specification allows only for one graphic format, WBMP, a one (1) bit version of the BMP (bitmap) format. Besides allowing only binary images, some image format standards and some displays only allow images of a limited number of pixels. In the WAP 1.1 standard, a WBMP image should not be larger than 150×150 pixels. Some WAP devices have screens that are very limited in terms of the number of pixels. For example, one WAP device has a screen that is 96 pixels wide by 65 pixels high. In order to render a digitized continuous tone input image using a binary output device, the image has to be converted to a binary image.

The process of converting a digitized continuous tone input image to a binary image so that the binary image appears to be a continuous tone image is known as digital halftoning.

In one type of digital halftoning processes, ordered dither digital halftoning, the input digitized continuous tone image is compared, on a pixel by pixel basis, to a threshold taken from a threshold array. Many ordered dither digital halftoning methods suffer from low frequency artifacts. Because the human vision system has greater sensitivity at low frequencies (less than 12 cycles/degree), such low frequency artifacts are very noticeable.

The visibility of low frequency artifacts in ordered dither digital halftoning methods has led to the development of methods producing binary images with a power spectrum having mostly higher frequency content, the so called “blue noise methods”.

The most frequently used “blue noise method” is the error diffusion method. In an error diffusion halftoning system, an input digital image In (the digitized continuous tone input image) is introduced into the system on a pixel by pixel basis, where n represents the input image pixel number. Each input pixel has its corresponding error value En−1, where En−1 is the error value of the previous pixel (n−1), added to the input value In at a summing node, resulting in modified image data. The modified image data, the sum of the input value and the error value of the previous pixel (In+En−1), is passed to a threshold comparator. The modified image data is compared to the constant threshold value T.O, to determine the appropriate output level On. Once the output level On is determined, it is subtracted from the modified image value to produce the input to an error filter. The error filter allocates its input, In−On, to subsequent pixels based upon an appropriate weighting scheme. Various weighting techniques may be used generate the error level E.n for the subsequent input pixel. The cyclical processing of pixels is continued until the end of the input data is reached. (For a more complete description of error diffusion see, for example, “Digital Halftoning”, by Robert Ulichney, MIT Press, Cambridge, Mass. and London, England, 1990, pp. 239-319).

Although the error diffusion method presents an improvement over many ordered dither methods, artifacts are still present. There is an inherent edge enhancement in the error diffusion method. Other known artifacts produced by the error diffusion method include artifacts called “worms” and “snowplowing” which degrade image quality.

In U.S. Pat. No. 5,045,952, Eschbach disclosed selectively modifying the threshold level on a pixel by pixel basis in order to increase or decrease the edge enhancement of the output digital image. The improvements disclosed by Eschbach do not allow the control of the edge enhancement by controlling the high frequency portion of the error. Also, the improvements disclosed by Eschbach do not introduce parameters that can be selected to produce the image of the highest perceptual quality at a specific output device.

In U.S. Pat. No. 5,757,976, Shu disclosed utilizing a set of error filters having different sizes for diffusing the input of the error filter among neighboring pixels in predetermined tonal areas of an image and adding “noise” to the threshold in order to achieve a smooth halftone image quality. The improvements disclosed by Shu do not introduce parameters that can be selected to produce the image of the highest perceptual quality at a specific output device.

SUMMARY OF THE INVENTION

It is the primary object of this invention to provide a method for generating a halftone image from a digitized continuous tone input image that provides adjustment of the local contrast of the resulting halftone image, minimizes artifacts and is easily implemented.

It is also an object of this invention to provide a method for generating a halftone image with parameters that can be selected to produce the image of highest quality at a specific output device.

To achieve the objects of this invention, one aspect of this invention includes an adaptive halftoning method where the difference between a digital image and a filtered digital image is introduced into the system on a pixel by pixel basis; each input difference pixel having a corresponding error value, generated from the previous pixels, added to the input value at a summing node, resulting in modified image difference data; the modified image difference data being passed to a threshold comparator where the modified image difference data is compared to a threshold value, the threshold value varying according to the properties of the digital image, to determine the appropriate output level; the output level is subtracted from the modified image difference value to produce the input to an error filter; the output of the error filter is multiplied by a adaptation coefficient, where the adaptation coefficient varies according to the properties of the digital image, to generate the error level for the subsequent input pixel; and, the cyclical processing of pixels is continued until the end of the input data is reached.

In another aspect of this invention, in the method described above, a histogram modification is performed on the image, and the difference between the histogram modified digital image and the filtered digital image is introduced into the system on a pixel by pixel basis.

In still another aspect of this invention, in the method described above, the histogram modification is performed on the difference between the digital image and the filtered digital image and the histogram modified difference is introduced into the system on a pixel by pixel basis.

In a further aspect of this invention, in the method described above, the selectively changing of the adaptation coefficient comprises dividing the difference between the value at the pixel and the filtered value at the pixel by the filtered value at the pixel, multiplying the absolute value of the result of the division by a first parameter, and adding a second parameter to the result of the multiplication, thereby obtaining the coefficient.

In still another aspect of this invention, in the method described above, the threshold calculation comprises multiplying the filtered value at the pixel by a third parameter.

In still another aspect of this invention, in the method described above and including the adaptation coefficient and threshold calculated as in the two preceding paragraphs, where the filter is a filter of finite extent, the extent of the filter, the first, second parameters and third parameters are selected to produce the image of the highest perceptual quality at a specific output device.

The methods, systems and computer readable code of this invention can be used to generate halftone images in order to obtain images of the highest perceptual quality when rendered on displays and printers. The methods, systems and computer readable code of this invention can also be used to for the design of computer generated holograms and for the encoding of the continuous tone input data.

DESCRIPTION OF THE DRAWINGS

The novel features that are considered characteristic of the invention are set forth with particularity in the appended claims. The invention itself, however, both as to its organization and its method of operation, together with other objects and advantages thereof will be best understood from the following description of the illustrated embodiment when read in connection with the accompanying drawings wherein:

FIG. 1a depicts a block diagram of selected components of an embodiment of a system, of this invention for generating a halftone image from a digitized continuous tone input image, where the histogram modification block is included after the summing node; and,

FIG. 1b depicts a block diagram of selected components of an embodiment of a system of this invention for generating a halftone image from a digitized continuous tone input image, where the histogram modification block is included before the summing node; and,

FIG. 1c depicts a block diagram of selected components of an embodiment of a system of this invention for generating a halftone image from a digitized continuous tone input image, where the adaptation coefficient multiplies the input to the error filter block; and

FIG. 2 depicts a block diagram of selected components of another embodiment of the system of this invention for generating a halftone image from a digitized continuous tone input image; and

FIG. 2a depicts a block diagram of selected components of another embodiment of the system of this invention for generating a halftone image from a digitized continuous tone input image, where the adaptation coefficient multiplies the input to the error filter block.

DETAILED DESCRIPTION

A method and system, for generating a halftone image from a digitized continuous tone input image, that provide adjustment of the local contrast of the resulting halftone image, minimizes artifacts, are easily implemented and contain parameters that can be selected on the basis of device characteristics like brightness, dynamic range, and pixel count, to produce the image of highest perceptual quality at a specific output device are disclosed.

A block diagram of selected components of an embodiment of a system of this invention for generating a halftone image from a digitized continuous tone input image (also referred to as a digital image) is shown in FIG. 1a. Referring to FIG. 1a, image input block 10 introduces an input digital image In into the system on a pixel by pixel basis, where n represents the input image pixel number. The input image is also provided to the filtering block 20. The output of filtering block 20 has the form
Avn32 h( . . . ,Ik, . . . , I.n, . . . )   (1)
where h is a functional form spanning a number of pixels. It should be apparent that the input digital image 10 can be a two dimensional array of pixel values and that the array can be represented as a linear array by using such approaches as raster representations or serpentine representation. For a two dimensional array of pixel values, the filter 20 will also be a two dimensional array of filter coefficients and can also be represented as a linear array. The functional forms will be shown in the one dimensional form for ease of interpretation.

In one embodiment: the output of the filtering block 20 has the form
Avn={Σn−N n+NIj}/(2N+1)   (2)
If the filtering block 20 comprises a linear filter, Avn will be given by a sum of terms, each term comprising the product of an input image pixel value multiplied by a filter coefficient.

It should be apparent that special consideration has to be given to the pixels at the boundaries of the image. For example, the calculations can be started N pixels from the boundary in equation (2). In that case the calculated and halftone image are smaller than the input image. In another case, the image is continued at the boundaries, the continuation pixels having the same value as the boundary pixel. It should be apparent that other methods of taking into account the effect of the boundaries can be used.

The output of the filtering block 20, Avn, is subtracted from the input digital image I.n at node 25, resulting in a difference value, Dn. In the embodiment in which histogram modification is not included, Dn is the input to a summing node 70. At the summing node 70, a corresponding error value En−1, where En−1 is the error value accumulated from the previous pixels, is added to the input value Dn resulting in a modified image datum. The modified image data, Dn+En−1, is compared to the output of the threshold calculation block 30 in the threshold comparison block 40 to produce the halftoning output, On. (In the case of a binary output device, if the modified image datum is above the threshold, the output level is the white level. Otherwise, the output level is the black level.) Once the output level On is determined, it is subtracted from the modified image value to produce the input to an error filter block 50. The error filter block 50 allocates its input, Dn+En−1−On, to subsequent pixels based upon an appropriate weighting scheme. The weighted contributions of the error filter block 50 input are stored and all the contributions to the next input pixel are summed to produce the output of the error filter block 50, the error value. The output of the error filter block 50, the error value, is multiplied by the adaptation coefficient in block 60 to generate the error level E.n for the subsequent input pixel. The cyclical processing of pixels, as further described below, is continued until the end of the input data is reached.

Referring again to FIG. 1, the input image is also provided to the threshold calculation block 30. The output of the threshold calculation block 30 has the form
t( . . . , Ik, . . . , I.n, . . . )   (3)
where t is a functional form spanning a number of pixels. The form in equation (3) allows the varying of the threshold according to properties of the digital image.

In one embodiment,
t( . . . ,Ik, . . . , I.n, . . . )=C0n−N n+NIj}/(2N+1)   (4)
In another embodiment, the output of the threshold calculation block is a linear combination of terms, each term comprising the product of an input image pixel value multiplied by a coefficient. It should be apparent that this embodiment can also be expressed as a function times a parameter.
The output of the threshold calculation block 30 is the threshold.

The first pixel value to be processed, IO, produces a difference value DO from summing node 25 and produces a value of DO out of summing node 70 (since E−1 is equal to 0). DO is then compared to the threshold producing an output of OO. At summing node 45, OO is subtracted from DO to produce the input to the error filter 50. The error filter 50 allocates its input, DO−OO, to subsequent pixels based upon an appropriate weighting scheme which determines how much the current input contributes to each subsequent pixel. Various weighting techniques may be used (see, for example, “Digital Halftoning” by Robert Ulichney, MIT Press, Cambridge, Mass. and London, England, 1990, pp. 239-319). The output of error filter 50 is multiplied by a adaptation coefficient 60. The adaptation coefficient 60 is the output of the coefficient calculation block 80. In one embodiment, the output of the coefficient calculation block 80 has the form
C1+C2abs{f( . . . ,Ik, . . . , I.n, . . . ,)/g( . . . ,Ik, . . . , I.n, . . . )}  (5)
where f and g are functional forms spanning a number of pixels. The form of Equation (5) allows the selective changing, of the coefficient according to the local properties of the digital image. C1 and C2 and the parameter in the threshold expression can be selected to produce the image of highest perceptual quality at a specific output device.

In another embodiment, the output of the coefficient calculation block 80 has the form
C1+C2{abs((I.n−({Σn−N n+NIj}/(2N+1)))/({Σn−N n+NIj}/(2N+1))))}  (6)

The input of error filter block 50 is multiplied by weighting coefficients and stored. All the contributions from the stored weighted values to the next pixel are summed to produce the out put of the error filter block 50. The output of the error filter block 50 is multiplied by the adaptation coefficient 60. The delay block 65 stores the result of the product of the adaptation coefficient 60 and the output of the error filter block 50. (In one embodiment, the Floyd-Steinberg filter, the input to the error filter is distributed according to the filter weights to the next pixel in the processing line and to neighboring pixels in the following line.) The output of delay block 65 is En−1 and is delayed by one pixel. (When the first pixel is processed, the output of the delay, EO, is added to the subsequent difference, D1.)

It should be apparent that the sequence order of error filter block 50 and the adaptation coefficient block 60 can be interchanged with similar results. In the embodiment in which the adaptation coefficient 60 multiplies the difference between the modified image datum and the output level, shown in FIG. 1c, the delay block 65 stores the output of the error filter block.

When the next pixel, I1, is introduced into the system from the image input block 10, it produces a difference value D1 from summing node 25 and produce a value of (D1+EO) out of summing node 70.

The above steps repeat for each subsequent pixel in the digital image thereby producing a halftone image, the sequence OO, O1, . . . , On. The modification of the threshold level and the adaptation coefficient allows control of the amount of edge enhancement and provides the opportunity to reduce artifacts.

In the embodiment in which histogram modification is included after the summing node 25, Dn is the input to the histogram modification block 75 and the output of the histogram modification block 75 is the input to the summing node 70. The above description follows if Dn is replaced by the output of the histogram modification block 75. It should be apparent that histogram modification operates on the entire difference image. (Histogram modification is well known to those skilled in the art. For a discussion of histogram modification, see, for example, Digital Image Processing, by William K. Pratt, John Wiley and Sons, 1978, ISBN 0-471-01888-0, pp. 311-318. For a discussion of histogram equalization, a form of histogram modification, see, for example, Digital Image Processing, by R. C. Gonzalez and P. Wintz, Addison-Wesley Publishing Co., 1977, ISBN 0-201-02596-3, pp. 119-126.)

In the embodiment in which histogram modification is included after the image input block 10, Dn is the difference between the output of the histogram modification block 75 (FIG. 1b) and the filtered image. The above description follows if In is replaced by the output of the histogram modification block.

The method described above produces improvements of the error diffusion method by utilizing the difference between the digital image and the filtered digital image as input into the system instead of the digital image, by multiplying the .the output of the error filter by the adaptation coefficient, where the adaptation coefficient varies according to the properties of the digital image, and by using a threshold value that varies according to the properties of the digital image to determine the appropriate output level.

Sample Embodiment

In a specific embodiment, shown in FIG. 2, the output of the filtering block 20, Avn, is given by Equation (2). The threshold calculation 30 is a function of the output of the filtering block 20 and is given by
t( . . . ,Ik, . . . , I.n, . . . )=COAvn   (7)
which is the same function as in Equation 4 when the output of the filtering block 20, Avn, is given by Equation (2). The output of the coefficient calculation block 80 depends on the output of the filtering block 20, Avn, and the difference Dn and is given by
C1+C2{abs((Dn−Avn)/Avn)}  (8)
When the output of the filtering block 20, Avn, is given by Equation (2), Equation (8) is the same as Equation (6).

Histogram equalization is included after the summing node 25. The processing of the input image pixels 10 occurs as described in the preceding section.

The value of N in Equation (2) (the extent of the filter), CO, C1, and C2 (first, second parameters and third parameters) can be selected to produce the image of highest perceptual quality at a specific output device. For a WBMP image on a specific monochrome mobile phone display, utilizing a Floyd-Steinberg error filter, the following parameters yield images of high perceptual quality:
N=7,
CO=−20,
C1=0.05, and
C2=1.
In another embodiment, shown in FIG. 2a, the sequence order of error filter block 50 and the adaptation coefficient block 60 are interchanged. In the embodiment of FIG. 2a, in which the adaptation coefficient 60 multiplies the difference between the modified image datum and the output level, the delay block 65 stores the output of the error filter block.

The embodiments described herein can also be expanded to include composite images, such as color images, where each color component might be treated individually by the algorithm. In the case of color input images, the value of N in Equation (2) (the extent of the filter), CO, C1, and C2 (first, second parameters and third parameters) can be selected to control the color difference at a color transition while minimizing any effects on the brightness at that location. Other possible applications of these embodiments include the design of computer generated holograms and the encoding of the continuous tone input data.

Although the embodiments described herein are most easily understood for binary output devices, the embodiments described herein can also be expanded to include rendering an output image when the number of gray levels in the image exceeds that of obtainable in the rendering device. It should be apparent how to expand the embodiments described herein to M-ary displays or M-ary rendering devices (see, for example, “Digital Halftoning” by Robert Ulichney, MIT Press, Cambridge, Mass., and London, England, 1990, p. 341).

It should be appreciated that the various embodiments described above are provided merely for purposes of example and do not constitute limitations of the present invention. Rather, various other embodiments are also within the scope of the claims, such as the following. The filter 20 can be selected to impart the desired functional behavior of the difference. The filter 20 can, for example, be a DC preserving filter. The threshold 40 and the adaptation coefficient 60 can also be selected to impart the desired characteristics of the image.

It should be apparent that Equations (4) and (5) are exemplary forms of functional expressions with parameters that can be adjusted. Functional expressions for the threshold and the adaptation coefficient ,where the expressions include parameters that can be adjusted, will satisfy the object of this invention.

In general, the techniques described above may be implemented, for example, in hardware, software, firmware, or any combination thereof. The techniques described above may be implemented in one or more computer programs executing on a programmable computer including a processor, a storage medium readable by the processor (including, for example, volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. Program code may be applied to data entered using the input device to perform the functions described and to generate output information. The output information may be applied to one or more output devices.

Elements and components described herein may be further divided into additional components or joined together to form fewer components for performing the same functions.

Each computer program within the scope of the claims below may be implemented in any programming language, such as assembly language, machine language, a high-level procedural programming language, or an object-oriented programming language. The programming language may be a compiled or interpreted programming language. Each computer program may be implemented in a computer program product tangibly embodied in a machine-readable storage device for execution by a computer processor. Method steps of the invention may be performed by a computer processor executing a program tangibly embodied on a computer-readable medium to perform functions of the invention by operating on input and generating output.

The generation of the halftone image can occur at a location remote from the rendering printer or display. The operations performed in software utilize instructions (“code”) that are stored in computer-readable media and store results and intermediate steps in computer-readable media.

Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CDROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read. Electrical, electromagnetic or optical signals that carry digital data streams representing various types of information are exemplary forms of carrier waves transporting the information.

Other embodiments of the invention, including combinations, additions, variations and other modifications of the disclosed embodiments will be obvious to those skilled in the art and are within the scope of the following claims.

Patent Citations
Cited PatentFiling datePublication dateApplicantTitle
US3820133Jul 24, 1972Jun 25, 1974C AdorneyTeaching device
US3864708Dec 4, 1973Feb 4, 1975Allen Brian SAutomatic photographic apparatus and postcard vending machine
US4070587Mar 19, 1976Jan 24, 1978Canon Kabushiki KaishaEnergizing control system for an intermittently energized device
US4072973Jan 26, 1976Feb 7, 1978Mayo William DCamera signal system for portrait taking
US4089017Sep 7, 1976May 9, 1978Polaroid CorporationAutomatic photostudio
US4154523May 31, 1977May 15, 1979Eastman Kodak CompanyExposure determination apparatus for a photographic printer
US4168120Apr 17, 1978Sep 18, 1979Pako CorporationAutomatic exposure corrections for photographic printer
US4284876Apr 7, 1980Aug 18, 1981Oki Electric Industry Co., Ltd.Thermal printing system
US4309712Dec 20, 1979Jan 5, 1982Canon Kabushiki KaishaThermal printer
US4347518May 29, 1981Aug 31, 1982Gould Inc.Thermal array protection apparatus
US4364063Feb 26, 1981Dec 14, 1982Tokyo Shibaura Denki Kabushiki KaishaThermal recording apparatus
US4385302Oct 16, 1981May 24, 1983Fuji Xerox Co., Ltd.Multicolor recording apparatus
US4391535Aug 10, 1981Jul 5, 1983Intermec CorporationMethod and apparatus for controlling the area of a thermal print medium that is exposed by a thermal printer
US4415908Jul 2, 1982Nov 15, 1983Canon Kabushiki KaishaThermal printer
US4443121Mar 1, 1983Apr 17, 1984Sony CorporationThermal printing apparatus with reference gray scale comparator
US4447818Feb 17, 1982May 8, 1984Fuji Xerox Co., Ltd.Multicolor heat-sensitive recording apparatus
US4464669Jun 16, 1982Aug 7, 1984Tokyo Shibaura Denki Kabushiki KaishaThermal printer
US4514738Nov 22, 1983Apr 30, 1985Tokyo Shibaura Denki Kabushiki KaishaThermal recording system
US4524368Mar 30, 1984Jun 18, 1985Fuji Xerox Co., Ltd.Thermal head drive circuit
US4540992Apr 7, 1983Sep 10, 1985Kabushiki Kaisha Daini SeikoshaThermal color transfer system
US4563691Dec 24, 1984Jan 7, 1986Fuji Xerox Co., Ltd.Thermo-sensitive recording apparatus
US4607262Jan 10, 1984Aug 19, 1986Fuji Xerox Co., Ltd.Thermal head drive circuit
US4638372Sep 26, 1984Jan 20, 1987Fuji Xerox Co., Ltd.Color copier
US4686549Dec 16, 1985Aug 11, 1987Minnesota Mining And Manufacturing CompanyReceptor sheet for thermal mass transfer printing
US4688051May 8, 1985Aug 18, 1987Ricoh Company, Ltd.Thermal print head driving system
US4704620Aug 28, 1986Nov 3, 1987Canon Kabushiki KaishaTemperature control system and ink jet printer utilizing the temperature control system
US4738526Nov 21, 1986Apr 19, 1988Autostudio CorporationAuto-portrait photo studio
US4739344Feb 27, 1987Apr 19, 1988Astro-Med, Inc.Chart recorded having multiple thermal print heads
US4777496May 26, 1987Oct 11, 1988Sony CorporationThermal printer with printing plate making mode
US4805033Apr 4, 1988Feb 14, 1989Olympus Optical Co., Ltd.Method of forming oblique dot pattern
US4809063May 26, 1988Feb 28, 1989Fuji Xerox Co., Ltd.Multicolor printing method using rectangular dither matrices of different size, shape, and arrangement of threshold values to minimize overlap of differently colored inks at lower gradations
US4884080Jun 2, 1987Nov 28, 1989Kabushiki Kaisha ToshibaColor image printing apparatus
US4907014May 18, 1989Mar 6, 1990Calcomp Inc.Safely retracting paper-cutting apparatus for a roll paper printer
US4933709Sep 25, 1989Jun 12, 1990Eastman Kodak CompanyAdjusting photographic printer color exposure determination algorithms
US4962403Dec 11, 1989Oct 9, 1990Eastman Kodak CompanyAdjusting photographic printer color exposure determination algorithms
US5006866Oct 12, 1989Apr 9, 1991Kabushiki Kaisha ToshibaThermal printing apparatus responsive to estimated stored heat of the heating element
US5045952Aug 21, 1989Sep 3, 1991Xerox CorporationMethod for edge enhanced error diffusion
US5046118Feb 6, 1990Sep 3, 1991Eastman Kodak CompanyTone-scale generation method and apparatus for digital x-ray images
US5066961Feb 12, 1990Nov 19, 1991Matsushita Electric Industrial Co., Ltd.Tonal printer utilizing heat prediction and temperature detection means
US5086306Jul 5, 1990Feb 4, 1992Ricoh Company, Ltd.Line head driving apparatus
US5086484Aug 21, 1989Feb 4, 1992Canon Kabushiki KaishaImage processing apparatus with fixed or variable threshold
US5109235Aug 1, 1989Apr 28, 1992Ricoh Company, Ltd.Recording density correcting apparatus
US5115252Jan 30, 1990May 19, 1992Eiichi SasakiThermal head drive apparatus correcting for the influence on a printing element of heat from other printing elements
US5130821Apr 16, 1990Jul 14, 1992Eastman Kodak CompanyMethod and apparatus for digital halftoning employing density distribution for selection of a threshold template
US5132703Mar 8, 1991Jul 21, 1992Yokogawa Electric CorporationThermal history control in a recorder using a line thermal head
US5132709Aug 26, 1991Jul 21, 1992Zebra Technologies CorporationApparatus and method for closed-loop, thermal control of printing head
US5162813Aug 30, 1990Nov 10, 1992Fuji Photo Film Co., Ltd.Method of and device for driving thermal head in printer
US5184150Aug 3, 1990Feb 2, 1993Sharp Kabushiki KaishaThermal printer for providing printed characters with a uniform density
US5208684Apr 24, 1991May 4, 1993Fujitsu LimitedHalf-tone image processing system
US5244861Jul 31, 1992Sep 14, 1993Eastman Kodak CompanyReceiving element for use in thermal dye transfer
US5248995Feb 24, 1992Sep 28, 1993Alps Electric Co., Ltd.Heat control method of a thermal head
US5268706Feb 12, 1992Dec 7, 1993Alps Electric Co., Ltd.Actuating control method of thermal head
US5285220Jun 25, 1992Feb 8, 1994Canon Kabushiki KaishaImage recording apparatus with tone correction for individual recording heads
US5307425Sep 1, 1992Apr 26, 1994Rohm Co., Ltd.Bi-level halftone processing circuit and image processing apparatus using the same
US5323245Feb 19, 1993Jun 21, 1994Minnesota Mining And Manufacturing CompanyPerpendicular, unequal frequency non-conventional screen patterns for electronic halftone generation
US5333246Apr 5, 1991Jul 26, 1994Seiko Epson CorporationPage-description language interpreter for a parallel-processing system
US5422662Mar 25, 1993Jun 6, 1995Nec CorporationThermal printer head having current sensors connected to heating elements
US5450099Apr 8, 1993Sep 12, 1995Eastman Kodak CompanyThermal line printer with staggered head segments and overlap compensation
US5455685Aug 31, 1992Oct 3, 1995Fuji Photo Film Co., Ltd.Video camera exposure control apparatus for controlling iris diaphragm and automatic gain control operating speed
US5469203Nov 24, 1992Nov 21, 1995Eastman Kodak CompanyParasitic resistance compensation for a thermal print head
US5479263Jul 1, 1993Dec 26, 1995Xerox CorporationGray pixel halftone encoder
US5497174Mar 11, 1994Mar 5, 1996Xerox CorporationVoltage drop correction for ink jet printer
US5521626Oct 12, 1993May 28, 1996Victor Company Of Japan, Ltd.Fusion-type thermal transfer printing system
US5539443Jul 2, 1993Jul 23, 1996Matsushita Electric Industrial Co., Ltd.Printer utilizing temperature evaluation and temperature detection
US5569347Dec 20, 1994Oct 29, 1996Fujicopian Co., Ltd.Receiver having micropores
US5576745May 24, 1994Nov 19, 1996Canon Kabushiki KaishaRecording apparatus having thermal head and recording method
US5602653Nov 8, 1994Feb 11, 1997Xerox CorporationPixel pair grid halftoning for a hyperacuity printer
US5617223Jun 28, 1995Apr 1, 1997Eastman Kodak CompanyImage scanner system and method for improved microfilm image quality
US5623297Jul 7, 1993Apr 22, 1997Intermec CorporationMethod and apparatus for controlling a thermal printhead
US5623581Jan 22, 1996Apr 22, 1997Apbi Interactive Kiosk SystemsDirect view interactive photo kiosk and image forming process for same
US5625399Jan 31, 1992Apr 29, 1997Intermec CorporationMethod and apparatus for controlling a thermal printhead
US5642148Nov 29, 1994Jun 24, 1997Nec CorporationThermal head apparatus with integrated circuits and current detection
US5644351Nov 30, 1993Jul 1, 1997Matsushita Electric Industrial Co., Ltd.Thermal gradation printing apparatus
US5646672Dec 14, 1995Jul 8, 1997Nec CorporationThermal head apparatus
US5664253Apr 4, 1996Sep 2, 1997Eastman Kodak CompanyStand alone photofinishing apparatus
US5668638Jun 27, 1996Sep 16, 1997Xerox CorporationError diffusion method with symmetric enhancement
US5694484May 15, 1995Dec 2, 1997Polaroid CorporationSystem and method for automatically processing image data to provide images of optimal perceptual quality
US5703644May 20, 1993Dec 30, 1997Matsushita Electric Industrial Co., Ltd.Automatic exposure control apparatus
US5706044Dec 20, 1995Jan 6, 1998Nec CorporationThermal head apparatus
US5707082Jul 18, 1995Jan 13, 1998Moore Business Forms IncThermally imaged colored baggage tags
US5711620Sep 26, 1996Jan 27, 1998Fuji Photo Film Co., Ltd.Color thermal printer
US5719615May 1, 1996Feb 17, 1998Kyocera CorporationApparatus for driving heating elements of a thermal head
US5721578Dec 27, 1994Feb 24, 1998Sharp Kabushiki KaishaMethods of gradation control and picture quality improvement in a thermal printer which adapts a staggered printing system
US5724456Mar 31, 1995Mar 3, 1998Polaroid CorporationBrightness adjustment of images using digital scene analysis
US5729274Apr 17, 1996Mar 17, 1998Fuji Photo Film Co., Ltd.Color direct thermal printing method and thermal head of thermal printer
US5757976Aug 8, 1996May 26, 1998Seiko Epson CorporationAdaptive filtering and thresholding arrangement for reducing graininess of images
US5777599Feb 14, 1992Jul 7, 1998Oki Electric Industry Co., Ltd.Image generation device and method using dithering
US5781315Nov 8, 1996Jul 14, 1998Fuji Photo Film Co., Ltd.Image processing method for photographic printer
US5784092Dec 23, 1994Jul 21, 1998Shinko Electric Co., Ltd.Thermal printer in which head energization period is controlled based on number of heads to be energized
US5786837Nov 7, 1995Jul 28, 1998Agfa-Gevaert N.V.Method and apparatus for thermal printing with voltage-drop compensation
US5786900Feb 17, 1995Jul 28, 1998Fuji Photo Film Co., Ltd.Image recording device for recording multicolor images with dot pitch pattern randomly arranged only in the sub-scanning direction
US5800075Apr 9, 1997Sep 1, 1998Fuji Photo Film Co., Ltd.Data processing method for eliminating influence of heat accumulating in thermal head
US5808653Apr 8, 1997Sep 15, 1998Matsushita Electric Industrial Co., Ltd.Thermal gradation printing apparatus
US5809164Mar 7, 1996Sep 15, 1998Polaroid CorporationSystem and method for color gamut and tone compression using an ideal mapping function
US5809177Jun 6, 1996Sep 15, 1998Xerox CorporationHybrid error diffusion pattern shifting reduction using programmable threshold perturbation
US5818474Jun 27, 1994Oct 6, 1998Canon Kabushiki KaishaInk-jet recording apparatus and method using asynchronous masks
US5818975Oct 28, 1996Oct 6, 1998Eastman Kodak CompanyMethod and apparatus for area selective exposure adjustment
US5835244Oct 7, 1996Nov 10, 1998Linotype-Hell AgMethod and apparatus for the conversion of color values
US5835627May 20, 1997Nov 10, 1998Higgins; Eric W.Digital image processing system
Non-Patent Citations
Reference
1"Adaptive Error Diffusion And Its Application In Multiresolution Rendenring", P. W. Wong, pp. 1184-1196, Jul. 1996, IEEE Trans. On Image Processing, vol. 5, No. 7, IEEE.
2"Adaptive Threshold Modulation For Error Diffusion Halftoning", N. Damera-Venkata and B. L. Evans, pp. 104-116, Jan. 2001, IEEE Trans. On Image Processing, vol. 10, No. 1, IEEE.
3"Digital Halftoning", R. Ulichney, pp. 239-319, pp. 341, 1987, Cambridge, MA, MIT Press.
4"Digital Image Processing", R. C. Gonzalez and P. Wintz, pp. 119-126, 1977, Reading, MA, Addison-Wesley.
5"Digital Image Processing", W.K. Pratt, pp. 311-318, 1978, New York, NY, J. Wiley & Sons.
6"Threshold Modulation In Error Diffusion", K. T. Know and R. Eschbach,pp. 185-192, Jul. 1993, vol. 2, No. 3, SPIE.
7Bhukhanwala et al., "Automated Global Enhancement of Digitalized Photographs," IEEE Transactions on Consumer Electronics, Feb. 1994.
8Damera-Venkata et al., "Adaptive Threshold Modulation for Error Diffusion Halftoning," IEEE Trans. On Image Processing, 2001, 10(1), 104-116.
9EP Communication issued by the Examining Division Apr. 2, 2004, EP1392514.
10EP Communication issued by the Examining Division Jan. 11, 2006, EP1597911.
11EP Communication issued by the Examining Division Jul. 7, 2009, EP1374557.
12EP Communication issued by the Examining Division May 23, 2006, EP1597911.
13EP Communication issued by the Examining Division May 29, 2009, EP1479220.
14EPC Application No. 1393544: Communication issued by the Examining Division dated Jan. 15, 2009, 7 pages.
15EPC Application No. 1597911: Communication issued by the Examining Division dated May 26, 2010, 8 pages.
16Gonzalez et al., "Digital Image Processing," Addison-Wesley, 1977, 119-126.
17Hann, R.A. et al., "Chemical Technology in Printing and Imaging Systems", The Royal Society of Chemistry, Special Publication. 133 (1993), pp. 73-85.
18Hann, R.A. et al., "Dye Diffusion Thermal Transfer (D2T2) Color Printing", Journal of Imaging Technology., 16 (6). (1990), pp. 238-241.
19International Application No. PCT/US02/015913: International Search Report mailed Oct. 11, 2002, 2 pages.
20International Application No. PCT/US02/018528: International Search Report mailed Oct. 31, 2002, 3 pages.
21International Application No. PCT/US02/18528: International Preliminary Examination Report (IPER) dated Apr. 4, 2003, 2 pages.
22International Application No. PCT/US04/020981: International Search Report mailed Mar. 15, 2005, 6 pages.
23International Preliminary Examination Report (IPER) dated Jan. 29, 2003, PCT/US02/008954.
24International Preliminary Examination Report (IPER) dated Jun. 30, 2003, PCT/US02/015546.
25International Preliminary Examination Report (IPER) dated Sep. 17, 2003, PCT/US02/015913.
26International Preliminary Examination Report (IPER) issued Jan. 3, 2006, PCT/US04/020981.
27International Preliminary Examination Report (IPER) issued Sep. 2, 2005, PCT/US04/004964.
28Japanese Application No. 2003-501190: Notice of Reasons of Rejection dated Dec. 15, 2006, 5 pages.
29Japanese Application No. 2008-096460: Notice of Reasons of Rejection dated Jul. 30, 2010, 4 pages.
30Japanese Application No. 2008-213280: Notice of Reasons of Rejection dated Feb. 5, 2010, 6 pages.
31Kearns et al., "Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation," XP-002299710, Jan. 1997, 1-20.
32Know et al., "Threshold Modulation In Error Diffusion," SPIE, 1993, 2(3), 185-192.
33Pratt, W.K., "Digital Image Processing," Wiley & Sons, 1978, 311-318.
34Taguchi et al., "New Thermal Offset Printing Employing Dye Transfer Technology (Tandem TOP-D)," NIP17: International Conference on Digital Printing Technologies, Sep. 2001, vol. 17, pp. 499-503.
35Ulichney, R., "Digital Halftoning," MIT Press, 1987, 239-319 p. 341.
36United States Patent and Trademark Office: Final Office Action dated Dec. 4, 2006, U.S. Appl. No. 10/375,440, filed Feb. 27, 2003.
37United States Patent and Trademark Office: Final Office Action dated Jan. 28, 2009, U.S. Appl. No. 10/611,737, filed Jul. 1, 2003.
38United States Patent and Trademark Office: Final Office Action dated Jul. 9, 2009, U.S. Appl. No. 11/546,633, filed Oct. 12, 2006.
39United States Patent and Trademark Office: Final Office Action dated Sep. 12, 2008, U.S. Appl. No. 10/844,286, filed May 12, 2004.
40United States Patent and Trademark Office: Non-Final Office Action dated Jan. 30, 2009, U.S. Appl. No. 11/546,633, filed Oct. 12, 2006.
41United States Patent and Trademark Office: Non-Final Office Action dated Jul. 13, 2006, U.S. Appl. No. 10/375,440, filed Feb. 27, 2003.
42United States Patent and Trademark Office: Non-Final Office Action dated Jul. 31, 2009, U.S. Appl. No. 12/031,151, filed Feb. 14, 2008.
43United States Patent and Trademark Office: Non-Final Office Action dated Jun. 10, 2009, U.S. Appl. No. 10/611,737, filed Jul. 1, 2003.
44United States Patent and Trademark Office: Non-Final Office Action dated Jun. 18, 2008, U.S. Appl. No. 10/611,737, filed Jul. 1, 2003.
45United States Patent and Trademark Office: Non-Final Office Action dated Mar. 20, 2008, U.S. Appl. No. 10/844,286, filed May 12, 2005.
46United States Patent and Trademark Office: Non-Final Office Action dated May 21, 2009, U.S. Appl. No. 10/844,286, filed May 12, 2004.
47United States Patent and Trademark Office: Non-Final Office Action dated Nov. 14, 2007, U.S. Appl. No. 10/844,286, filed May 12, 2004.
48United States Patent and Trademark Office: Non-Final Office Action dated Nov. 29, 2004, U.S. Appl. No. 09/817,932, filed Mar. 27, 2001.
49United States Patent and Trademark Office: Non-Final Office Action dated Nov. 29, 2004, U.S. Appl. No. 09/870,537, filed May 30, 2001.
50United States Patent and Trademark Office: Non-Final Office Action dated Oct. 2, 2004, U.S. Appl. No. 10/080,833, filed Feb. 22, 2003.
51United States Patent and Trademark Office: Non-Final Office Action dated Oct. 4, 2007, U.S. Appl. No. 10/611,737, filed Jul. 1, 2003.
52United States Patent and Trademark Office: Non-Final Office Action dated Sep. 22, 2003, U.S. Appl. No. 10/078,644, filed Feb. 19, 2002.
53United States Patent and Trademark Office: Notice of Allowance dated Aug. 31, 2005, U.S. Appl. No. 09/817,932, filed Mar. 27, 2001.
54United States Patent and Trademark Office: Notice of Allowance dated Feb. 22, 2005, U.S. Appl. No. 10/078,644, filed Feb. 19, 2002.
55United States Patent and Trademark Office: Notice of Allowance dated May 29, 2007, U.S. Appl. No. 10/375,440, filed Feb. 27, 2003.
56United States Patent and Trademark Office: Notice of Allowance dated May 9, 2005, U.S. Appl. No. 09/870,537, filed May 30, 2001.
57United States Patent and Trademark Office: Notice of Allowance dated Sep. 23, 2004, U.S. Appl. No. 10/080,883, filed Feb. 22, 2003.
58United States Patent and Trademark Office: Notice of Allowance dated Sep. 6, 2007, U.S. Appl. No. 10/375,440, filed Feb. 27, 2003.
59United States Patent and Trademark Office: Restriction Requirement dated Jun. 29, 2007, U.S. Appl. No. 10/611,737, filed Jul. 1, 2003.
60United States Patent and Trademark Office: Restriction Requirement dated May 26, 2009, U.S. Appl. No. 11/546,633, filed Oct. 12, 2006.
61United States Patent and Trademark Office: Restriction Requirement dated Oct. 2, 2003, U.S. Appl. No. 10/080,883, filed Feb. 2, 2002.
62United States Patent and Trademark Office: Restriction Requirement dated Oct. 8, 2008, U.S. Appl. No. 11/546,633, filed Oct. 12, 2006.
63United States Patent and Trademark Office: Restriction Requirement dated Sep. 30, 2003, U.S. Appl. No. 10/078,644, filed Feb. 19, 2002.
64United States Patent and Trademark Office: Restriction Requirement dated Sep. 4, 2007, U.S. Appl. No. 10/844,286, filed May 12, 2004.
65United States Patent and Trademark Office: U.S. Appl. No. 12/031,151, filed Feb. 14, 2008, Bybell.
66Weston et al., "Adaptive Margin Support Vector Machines," Advances in Large Margin Classifiers, 2000, 281-296.
67Wong, P.W., "Adaptive Error Diffusion and Its Application in Multiresolution Rendering," IEEE Trans. On Image Processing, 1996, 5(7), 1184-1196.
Classifications
U.S. Classification358/1.9, 382/252, 358/3.05, 358/3.03, 358/3.04
International ClassificationH04N1/405, G06T5/40, G06T3/40, B41J2/52, G06T5/20
Cooperative ClassificationH04N1/4053
European ClassificationH04N1/405B2B
Legal Events
DateCodeEventDescription
Jun 18, 2013ASAssignment
Owner name: INTELLECTUAL VENTURES I LLC, DELAWARE
Free format text: MERGER;ASSIGNOR:SENSHIN CAPITAL, LLC;REEL/FRAME:030639/0279
Effective date: 20130212
Jan 25, 2013FPAYFee payment
Year of fee payment: 8
Oct 11, 2011CCCertificate of correction
Mar 3, 2011ASAssignment
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNOR:POLAROID CORPORATION;REEL/FRAME:025898/0659
Effective date: 20070205
Owner name: SENSHIN CAPITAL, LLC, DELAWARE