US 20040264794 A1 Abstract In a method and a device for transmission of S+P transform coded digitized images a mask is calculated by means of which a region of interest (ROI) can be transmitted lossless whereby the ROI can be transmitted and received lossless and still maintaining a good compression ratio for the image as a whole. This is possible since no or very few bits can be used for the remaining part of the image. The calculated mask can also be used for transmitting the coefficients needed for a lossless region of interest during any stage of the transmission.
Claims(31) 1-10. (Canceled). 11. A method of receiving and decompressing an image including at least one Region of Interest (ROI), comprising:
requesting the image; reading information from a received code stream describing the ROI in the image; using the information to identify wavelet transform coefficients needed to reconstruct the ROI; and transforming the identified wavelet transform coefficients into an image domain using a wavelet transform to obtain a lossless reconstruction of the ROI. 12. A method according to 13. A method according to requesting a new ROI during or after receiving the image. 14. A method according to 15. A method according to 16. A method according to 17. A device for receiving and decompressing an image including at least one Region of Interest (ROI), comprising electronic circuitry configured to perform the following tasks:
request the image; read information from a received code stream describing the ROI in the image; use the information to identify wavelet transform coefficients needed to reconstruct the ROI; and transform the identified wavelet transform coefficients into an image domain using a wavelet transform to obtain a lossless reconstruction of the ROI. 18. A device according to 19. A device according to 20. A device according to 21. A device according to 22. A device according to 23. A device for receiving and decompressing an image including at least one Region of Interest (ROI), comprising:
means for requesting the image; means for reading information from a received code stream describing the ROI in the image; means for using the information to identify wavelet transform coefficients needed to reconstruct the ROI; and means for transforming the identified wavelet transform coefficients into an image domain using a wavelet transform to obtain a lossless reconstruction of the ROI. 24. A device according to 25. A device according to means for requesting a new ROI during or after receiving the image. 26. A device according to 27. A device according to 28. A device according to 29. A method for lossless transmission of a region of interest, comprising:
wavelet transforming an image that includes a region of interest; selecting wavelet transform coefficients from the wavelet transformed image corresponding to the ROI; calculating an ROI mask of wavelet transform coefficients using the selected wavelet transform coefficients; and transmitting the ROI mask to a receiver, wherein the ROI mask permits the receiver to reconstruct the ROI losslessly. 30. The method in 31. The method in formulating a new ROI; selecting new wavelet transform coefficients from the wavelet transformed image corresponding to the new ROI; calculating a new ROI mask of wavelet transform coefficients using the new wavelet transform coefficients; and transmitting the new ROI mask to a receiver. 32. The method in 33. An apparatus for lossless transmission of a region of interest (ROI), comprising:
means for wavelet transforming an image that includes a region of interest; means for selecting wavelet transform coefficients from the wavelet transformed image corresponding to the ROI; means for calculating an ROI mask of wavelet transform coefficients using the selected wavelet transform coefficients; and means for transmitting the ROI mask to a receiver, wherein the ROI mask permits the receiver to reconstruct the ROI losslessly. 34. The apparatus in 35. The apparatus in means for formulating a new ROI; means for selecting new wavelet transform coefficients from the wavelet transformed image corresponding to the new ROI; means for calculating a new ROI mask of wavelet transform coefficients using the new wavelet transform coefficients; and means for transmitting the new ROI mask to a receiver. 36. The apparatus in 37. An apparatus for lossless transmission of a region of interest (ROI), comprising electronic circuitry configured to perform the following tasks:
wavelet transform an image that includes a region of interest; select wavelet transform coefficients from the wavelet transformed image corresponding to the ROI; calculate an ROI mask of wavelet transform coefficients using the selected wavelet transform coefficients; and transmit the ROI mask to a receiver, wherein the ROI mask permits the receiver to reconstruct the ROI losslessly. 38. The apparatus in 39. The apparatus in formulate a new ROI; select new wavelet transform coefficients from the wavelet transformed image corresponding to the new ROI; calculate a new ROI mask of wavelet transform coefficients using the new wavelet transform coefficients; and transmit the new ROI mask to a receiver. 40. The apparatus in Description [0001] The present invention relates to a method and a device for lossless coding of a region of interest (ROI) in transmission of a still image. The method and the device are particularly well suited for the S+P transform. [0002] In transmission of digitized still images from a transmitter to a receiver, the image is usually coded in order to reduce the amount of bits required for transmitting the image. [0003] The reason for reducing the amount of bits is usually that the capacity of the channel used is limited. A digitized image, however, consists of a very large number of bits. When transmitting such an image, consisting of a very large number of bits, over a channel, which has a limited bandwidth, transmission times for most applications become unacceptably long, if every bit of the image has to be transmitted. [0004] Therefore, much research efforts in recent years have concerned coding methods and techniques for digitized images, aiming at reducing the number of bits necessary to transmit. [0005] These methods can be divided into two groups: [0006] Lossless methods, i.e. methods exploiting the redundancy in the image in such a manner that the image can be reconstructed by the receiver without any loss of information. [0007] Lossy methods, i.e. methods exploiting the fact that all bits are not equally important to the receiver, hence the received image is not identical to the original, but looks, e.g. for the human eye, sufficiently alike the original image. [0008] Furthermore, in some applications a part of a transmitted image may be more interesting than the rest of the image and a better visual quality of this part of the image is therefore desired. Such a part is usually termed region of interest (ROI). An application in which this can be useful is for example medical databases. In some cases it is also desired or required that the region of interest is transmitted lossless, while the quality of the rest of the image is of less importance. [0009] One method, which can be used, for coding of still images is the wavelet based S+P transform. The S+P transform is completely reversible and can be performed directly without memory expansion. The S+P transform is described in A. Said and W. A. Pearlman, ‘Reversible image compression via multiresolution representation and predictive coding’, in Proc. SPIE Conf. Visual Communications and Image Processing '93, Cambridge, Mass., Nov. 1993, Proc. SPIE 2094, pp. 664-674, which is incorporated herein by reference. [0010] It consists of the S transform, see V. K Heer and H-E. Reinfelder, ‘A comparison of reversible methods for data compression’, Proc. SPIE, vol. 1233 Med. Imag. IV, pp 354-365, 1990., which also is incorporated herein by reference and which is a pyramid sub band decomposition, and of a prediction used to take out the remaining redundancies from the high frequency sub bands. The forward transformation is done by applying a subband decomposition several times. The inverse is found by applying the corresponding compositions in reverse order. [0011] In J. Ström, P. C. Cosman, ‘Medical image compression with lossless regions of interest’, Signal Processing 59, Nr 2, Jun. (1997) 155-171 it is described how a lossless region of interest can be calculated for the S transform. [0012] However, when trying to apply such a technique to the wavelet based S+P transform, i.e. lossless transmission of the region of interest and a lossy transmission of the rest of the image, no straightforward technique can be used. [0013] Thus, today there exist no way for lossless region of interest coding of an S+P transformed image. This is due to the fact that it is not easy to select the information in the S+P transformation coded original image which should be transmitted in order to obtain a perfect, lossless reconstruction of the region of interest, without having to transmit the entire image lossless. [0014] It is an object of the present invention to solve the problem of how to select the data in an S+P transformed image in order to achieve a lossless region of interest in a receiver. [0015] This object is obtained by means of calculating a mask for the region of interest as will be described below. [0016] Thus, in order to achieve a perfectly reconstructed region of interest, while maintaining a fair amount or compression, bits need to be saved by sending less information about the background or the part of the image which is not interesting, or at least wait with that information until a later stage in the transmission. [0017] To do this, a lossless mask is calculated. The mask is a bit plane indicating which wavelet coefficients have to be exactly transmitted if the receiver should be able to reconstruct the desired region perfectly. In the case that an ROI in the image is chosen to be lossless, the A-predictor used in the S+P transform referred to above should be used. [0018] This is because when the A-predictor is used no prediction of high frequencies is performed with the help of high frequencies. If this was the case, like in the C-predictor case, see the reference above, a possible error might propagate all the way to the edge of the image, and also inside the ROI, making it unfeasible to provide a lossless ROI. [0019] The mask is calculated following the same steps as the forward S+P transform, i.e. tracing the inverse transform backwards. To start out with, the mask is a binary map of the ROI, so that it is 1 inside the ROI and 0 outside. In each step it is then updated line by line and then column by column. In each step the mask is updated so that it will indicate which coefficients are needed exactly at this step, for the inverse S+P to reproduce the coefficients of the previous mask exactly. [0020] The last step of the inverse S+P is a composition of two sub bands. To trace this step backwards, the coefficients in the two sub bands that are needed exactly are found. The second last step is a composition of four sub bands into two. To trace this step backwards, the coefficients in the four sub bands that are needed to give a perfect reconstruction of the coefficients included in the mask for two sub bands are found. [0021] All steps are then traced backwards to give a mask that implicates the following: [0022] If the coefficients corresponding to the mask are transmitted and received exactly, and the inverse S+P (with the A-predictor) calculated on them, the desired ROI will be reconstructed perfectly. [0023] To trace a step backwards on a separate line, where X [0024] For the S+P with the A predictor:
[0025] Thus, the binary mask for the low frequency sub band and the high frequency sub band, respectively is set to a binary one, i.e. the corresponding coefficient is to be transmitted in order to obtain a lossless region of interest, if the above conditions are fulfilled. [0026] For synchronisation, the same mask is found both in the encoder and the decoder. After a certain stage, skipping can be switched on and background list entries detected. These are the ones corresponding to sets containing no coefficients that are indicated for exact transmission by the lossless mask. [0027] The background list entries can then be skipped totally, put in a wait list for later improvement or given a lower priority in some kind of interleaving scheme. [0028] Furthermore, the shape of the ROI does not have to be defined before the transmission and can therefore be specified either by the transmitter or the receiver at any stage of the transmission. [0029] The ROI can also be formed by two or more parts, which are not in contact with each other. The technique is then applied in the same manner. [0030] The present invention will now be described in more detail by way of a non-limiting examples and with reference to the accompanying drawings, in which: [0031]FIG. 1 is a general transmission system employing the S+P transform. [0032]FIGS. 2 [0033]FIGS. 3 [0034] In FIG. 1 a general transmission system employing the S+P transform is shown. The system comprises an S+P coder block [0035] The information is then forwarded to the ROI block [0036] In FIGS. 2 [0037] Thus, in the ROI block [0038] Next, in a block [0039] Next, in a block [0040] In the block [0041] Thereupon, in a block [0042] In the block [0043] In FIG. 2 [0044] Thus, if the mask before the step inversion is a binary one for (2n−2), (2n−1), (2n), (2n+1), (2n+2) or (2n+3), the procedure proceeds to a block [0045] In the block [0046] In the block [0047] In the block [0048] The method of calculating the lossless mask for the region of interest can also be expressed as pseudo code as is shown below.
[0049] In FIGS. 3 [0050] In FIG. 3 [0051] In the FIGS. 3 [0052] In another preferred embodiment the prediction is extended to using the low frequency coefficients L(n−2), L(n−1), L(n) , L(n+1), L(n+2) . The prediction is therefore: [0053] For example if the coefficients are: [0054] the filter is identical to the Two-Ten transform used in the CREW as described in RICOH CREW Image Compression Standard Version 0.11 (Draft 11), 24 Oct. 1997, RICOH Silicon Valley, Inc. If the coefficients an−2 and an+2 are equal to 0 the predictor will be the A-predictor. Predictors using more coefficients are also possible. [0055] The mask that is found by a backward trace is now slightly extended. To trace a step backwards on a separate line in this case, where X [0056] For the extended predictor:
[0057] Simple pseudo code for calculating the extended mask is shown below.
[0058] Also, it is possible to change the form, size and location of the region of interest during transmission when using the method and device as described herein. The only steps that need to be performed is transmission of a request for another region of interest from the receiver to the transmitter, which then can calculated a new mask corresponding to the new region of interest and then transmit the coefficient corresponding to this new mask to the receiver. The request for another region of interest can also be generated at another location than in a receiver, for example by a program in the transmitter. [0059] Such a function can be very useful in many applications. It is, for example, not always that the receiver receives the region of interest that he/she desires. In that case he/she can transmit a request for a larger region of interest or even a completely different region of interest. [0060] Therefore, in a preferred embodiment, the transmitter is provided with means for receiving a new region of interest from, for example, a receiver during transmission of an image, and for calculating a mask corresponding to such a new region of interest. A new region of interest can then be transmitted from the transmitter to the receiver. [0061] Thus, a method and a device for transmission of S+P transform coded digitized images using a mask by means of which a region of interest (ROI) can be transmitted lossless without having to transmit the remaining part of the digitized image has been described. The use of the mask makes it possible to transmit and receive the ROI lossless and still maintaining a good compression ratio for the image as a whole. This is possible since no or very few bits can be used for the remaining part of the image. [0062] Furthermore, a mask calculated according to the principles described herein can be used for transmitting the coefficients required for obtaining a lossless ROI at any time during the transmission. Referenced by
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