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Definitions

• Lossy compression methods are methods wherein there is a certain amount of loss of fidelity of the image; in other words, close inspection of the reproduced image would show a loss of fidelity of the image.
• Lossless compression methods are ones where the original image is reproduced exactly after decoding.
• the present invention is directed to an efficient image compression method and apparatus wherein part of an image can be compressed with a higher level of fidelity in the reproduced image than other parts of the image, based on a selection of a region-of-interest by the user who is initially encoding or compressing the image, or the user who receives and decodes the image data through interaction with the encoding side.
• a currently popular standard for compressing images is called the
• JPEG or "J-peg” standard This standard was developed by a committee called The Joint Photographic Experts Group, and is popularly used to compress still images for storage or network transmission.
• Recent papers by Said and Pearlman discuss new image coding and decoding methods based upon set partitioning in hierarchical trees (SPIHT). See Said and Pearlman, Image Codec Based on Set Partitioning in Hierarchical Trees, IEEE Transactions on Circuits and Systems for Video Technology, vol. 6, no. 3, June 1996, and Said and Pearlman, Image Multi-Resolution Representation, IEEE Transactions on Image Processing, vol. 5, no. 9, September 1996. The contents of these papers are hereby incorporated by reference.
• N is the number of image pixels, and the above calculation for mean squared-error distortion can therefore be made.
• the mean squared-error distortion measure decreases by
• An algorithm is utilized by the encoder to send a value representing the maximum pixel value for a particular pixel coordinate, sorting pixel coordinates by wavelet transform coefficient values, then outputting a most significant bit of the various coefficients, using a number of sorting passes and refinement passes, to provide high quality reconstructed images utilizing a small fraction of the transmitted pixel coordinates.
• a user can set a desired rate or distortion by setting the number of bits to be spent in sorting passes and refinement passes.
• a spatial orientation tree as shown in Figure 1 , pixel information is separated into a List of Insignificant Sets (LIS), a list of insignificant pixels (LIP), and a List of Significant Pixels (LSP).
• Figure 1 illustrates image 100, with a plurality of pixel sets 101 , 102, 10x therein.
• the spatial orientation tree is developed as known in the art, by decomposition of integer-valued or non-integer-valued wavelet transform (WT) coefficients. Coefficients in the LH subband of each decomposition level forms the spatial orientation tree.
• parent node 101 has a series of roots and offspring nodes 102-107.
• the LIP is a list of coordinates of insignificant pixel or WT coefficients
• the LIS is a list of coordinates of tree roots with insignificant descendent sets, with multiple types of entries on the list (Type A and Type B)
• the LSP is a list of coordinates of significant pixels.
• Sorting and partitioning of the list contents is performed as illustrated in Figure 2.
• the significance determination which is made in the flow chart of Figure 2 is based upon a given significance threshold entries from the LIP which are determined to be significant at 202 LSP, 203, and entries which are determined not to be significant at 202 are returned to the LIP for testing during subsequent passes. If it is determined that all LIP entries have been tested at 204, then LIS entries begin to be tested. If all LIP entries are not tested, a next LIP entry is tested for significance at 202.
• LIS entries at 205 are tested at 206 to determine whether the LIS entries are type A, which are sets of coordinates of descendants of a node, or type B if the entry represents a difference between coordinates of descendants and offspring. If the sets are determined to be type A, significance is tested at 207. If significant, the set is partitioned at 208 into offspring and descendants of offspring with offspring being tested for significance at 209. If significant, the coordinate is placed on the LSP. If insignificant, the tested offspring is moved to the end of the LIP. If the initial type A entry is determined to be insignificant at 207, the entry is returned to the LIS.
• Type B LIS entries are tested for significance at 210, and moved to the LIP if significant or returned to the LIS if insignificant. After each test for significance, a one is output if the entry is determined to be significant, and a zero is output if the entry is determined to be insignificant. The ones and zeros are used to indicate when a specified number of bits have been output for termination purposes. Decoding occurs in a same, but reversed fashion. Entries of each list are identified by the pixel coordinates, with the LIP and LSP representing individual pixels, and the LIS representing sets of coordinates, with the sets of coordinates being grouped according to their status as either coordinates of a descendent of a node of the spatial orientation tree.
• sorting passes are performed until reaching the selected termination point, with an increase in sorting passes providing a decrease in distortion due to further refinement provided by more accurate significance classification. Increased sorting passes, however, requires additional time.
• the decoder duplicates the encoder's execution path in reverse to sort the significant coefficients, with "outputs" being changed to "inputs" for decoding, to recover appropriate ordering information.
• the coding method of the prior art therefore, attempts to mathematically determine an area of the image which should have a higher fidelity or lower loss than areas of the image based upon the significance determinations.
• Figure 3 illustrates an important aspect of the SPIHT coding, which is repetitive sorting passes and refinement passes for a given threshold; sorting and refinement is repeated until encoding is complete.
• the present invention is directed to an image encoding and decoding method and apparatus which enables a user to set a region-of- interest (ROI) for higher fidelity or lower loss compression than other areas of the image.
• ROI region-of- interest
• the invention incorporates a new feature for ROI coding without compromising any capabilities of the image coding method into which the ROI coding is incorporated, such as progressive by fidelity, progressive by resolution, progressive by fidelity and resolution, and lossy/lossless capabilities. Furthermore, computational complexity increase due to the implementation of the invention is minimal.
• the encoder output according to the prior art is a bit stream with a sequential series of bits which is ordered to reduce the overall mean squared error.
• the invention is a method and apparatus which modifies the ordering of the bit stream output such that additional emphasis is placed on the region-of-interest, than other aspects of the image. In applications such as medical imaging or virtually any other type of imaging, the region of interest may not be the pixel values having the highest-ordered coefficients in a sense of reducing the MSE.
• the present invention therefore, enables a user at a transmitting end or receiving end to select an appropriate region of interest which is reconstructed possibly losslessly and with a higher fidelity than the rest of the image, regardless of the importance of the region of interest in the MSE sense.
• Figure 1 illustrates an aspect of a spatial-orientation tree, according to the prior art
• FIG. 2 is a flow chart which illustrates a brief explanation of SPIHT compression according of the prior art
• FIG. 3 is a summarization flow chart which illustrates the prior art
• Figure 4 is a flow chart which explains region-of-interest image coding according to the present invention.
• Figure 5 is a graph which illustrates the speed of lossless reconstruction as a function of left-bit-shifts according to the present invention
• FIG. 6 illustrates the PSNR performance of the present invention
• Figure 7 illustrates a result of the invention utilizing particular reconstruction rates
• Figure 8 is a photo of a lossless reconstruction of the same photo with the same region of interest as Figure 7;
• Figures 9A and 9B illustrate the rate-distortion penalty associated with a coding method according to the present invention
• Figure 10 is a block diagram which illustrates a series of blocks which are utilized to implement the invention wherein ROI selection is performed on the encoding side; and 7
• FIG. 11 is a block diagram which illustrates elements utilized to implement the invention wherein ROI selection is performed on-line.
• the present invention is directed to a method and apparatus of performing still image compression wherein either a user at the transmitting side can specify what is, in his or her opinion, a region-of-interest before the encoding process, or wherein a user on the receiving side can determine the region of interest based upon the incoming bit stream and identify the desired area to place more emphasis on the region of interest during the remainder of the encoding process.
• a user on the transmitting side is determining the ROI
• encoding can be performed off-line.
• a user on the receiving side is identifying the ROI, encoding must be performed on-line.
• WT wavelet transform
• the compression method can be, for example, the SPIHT method of Said and Pearlman; for the purposes of this description, the SPIHT method will be referred to as an example, but this invention is not to be interpreted as being limited to SPIHT applications.
• the scaling up discussed previously is performed by the selected coefficients being given higher priority through a fixed number of left bit shifts, with each left bit shift corresponding to a scaling up or increase in bit significance by a factor of two in each subband. The larger number of left shifts, the higher the emphasis will be on the WT coefficients, and the more noticeable will be the speed increase of the ROI reconstruction.
• the encoder or decoder according to the invention therefore, can select the region of interest, and dictate the speed with which the region of interest is reconstructed, or the amount of additional emphasis the region of interest receives with respect to the rest of the image.
• FIG. 4 illustrates the ROI coding of the present invention in a compression method such as SPIHT.
• ROI selection occurs at 400.
• the ROI coefficients are scaled up at 401 , for a given threshold level.
• Sorting passes and refinement passes are performed on the ROI image data at 402 and 403, respectively.
• the region of interest is selected along with a value of S, and the selected ROI and S value are fed back to the encoder.
• the encoder selects the ROI and S, and encoding can be performed off line or on-line. All WT coefficients relating to the region of interest (ROI coefficients) are then identified, and left shifted by S bits.
• region of interest is arbitrary, as long as the overall region of interest can be described or defined as a plurality of adjacent rectangles or as a non- adjacent collection of pluralities of adjacent rectangles.
• the region of interest can be a single region of interest, or there can be a plurality of regions of interests which can be handled in the same manner discussed herein.
• WT coefficients associated with reconstruction of the region of interest are identified in the wavelet transform domain, and only these WT coefficients are encoded/decoded according to a compression method which becomes modified to concentrate on encoding/decoding of the specified coefficients. Corresponding coefficients, therefore, are encoded/decoded at an earlier threshold cycle or earlier path than the highest priority coefficients according to the compression method such as the SPIHT.
• ROI coefficients are identified through tracing back of the inverse wavelet transform from the image domain to the WT coefficient domain. Inverse wavelet transformation converts image representation in the WT coefficient domain into image data in the image domain. One pixel in the image is reconstructed with a couple of WT coefficients through inverse wavelet transformation. Therefore, once the region-of-interest is specified in the image domain, WT coefficients pertaining thereto, noted as ROI coefficients, are identified by tracing back the inverse wavelet transform from the image domain to the WT domain.
• the left-shifting discussed above refers to scaling the WT coefficients by a left bit shift, which corresponds to scaling by 2, 4, 8, etc., in accordance with known binary shifting.
• a conventional method such as the SPIHT coding algorithm handles the WT coefficients from the highest non-zero bit fields of 10 all coefficients (MSB), to the least significant bit (LSB). Scanning all coefficients in sequential bit depth from the MSB to the LSB as a path results in information ordering being achieved in a comparable manner.
• Coding the region-of-interest orders information by scaling up the WT coefficients pertaining to the region of interest such that they are handled or visited in an earlier path or cycle, thereby placing the ROI coefficients in an earlier portion of the encoding bit stream. The larger the left bit shift, the earlier in the bit stream the ROI coefficients are placed. Therefore, the higher the left shift value, the higher the speed of reconstruction of the region-of-interest.
• the amount of losslessness of the image reconstruction is based upon the wavelet transform with which the compression method generates the encoding bit stream.
• the encoding bit stream generates images of a wide variety of bit rates, including ones which assure losslessness of the overall image.
• the reconstruction is to be considered a "lossy" reconstruction. The lower the bit rate at which the coding process is terminated, the more lossy the reconstruction result will be. Therefore, if the coding for the region of interest coefficients are terminated early, the reconstruction results of the region-of-interest would also be lossy, although with a higher level of emphasis than areas outside of the region-of-interest.
• the region-of-interest coding works in the same manner as discussed above, with the exception of the fact that the reconstructed result can never be considered to be lossless, due to the fact that the wavelet transform and quantization associated therewith generates some loss which can never be recovered. 11
• FIG. 5 and 6 are graphs which illustrate performance results on a 512 x 512 image, with the region of interest illustrated by the rectangular section of Figure 7.
• the region of interest is a 128 x 128 square containing a portion of the image.
• the speed of lossless reconstruction of the region of interest varies as a function of the number of left shift values S.
• PSNR peak signal-to-noise ratio
• the PSNR of this image is 29.22 dB at 0.389 bpp.
• a region of interest coding technique provides an effective and flexible system for embedded ROI image encoding, with flexibility from varying levels of lossy coding all the way up to lossless ROI image coding.
• Lossless 12 reconstruction of the region of interest and an effective or "subjectively lossless" reconstruction of the remainder of the image can be achieved at a bit rate of 3-4 times smaller what is needed for lossless reconstruction of the overall image.
• Figures 9(a) and 9(b) illustrate the rate-distortion penalty which is associated with a coding method and apparatus according to the present invention.
• the methods discussed above include numerous embodiments for image compression wherein the selection of the region of interest can either be performed before encoding in an off-line situation, or during encoding in an on-line manner.
• the selection can be performed on the receiving side wherein the receiving side sends information to the encoding or transmitting side regarding the region-of-interest, and sorting and prioritization is adjusted accordingly.
• the on-line selection can also be performed by the encoding side, if the encoding side includes a local decoder which simulates a decoding process before transmission or storage of the data.
• the invention can be embodied in a computer system comprising a display, a central processing unit, memory, and appropriate communication means such as a modem and a telephone line, which are configured to provide an input means for inputting digital image data, such that the display means can display the digital image data.
• the computer system can be configured to function such that a 13 selecting device or selecting means is connected to the display for selecting the region of interest.
• a sorting and prioritizing means or device can be connected to the selecting device for sorting and prioritizing the digital image data according to at least two priority categories, with digital image data corresponding to the region of interest having a higher priority than the digital image data which corresponds to areas outside of the region of interest.
• the communication circuitry or device can function as a transmitting device for transmitting the sorted and prioritized data to a remote location, with the transmitting device transmitting the digital image data corresponding to the region of interest with a higher priority than the areas outside of the region of interest.
• the transmitted data is received by a receiving computer which would include a receiving means or device for receiving the transmitted data, and a reconstructing device for reconstructing the transmitted data.
• the reconstructing device would include a decoding device for decoding the sorted and prioritized digital image data.
• the region of interest is reconstructed by the reconstructing device at a faster rate than the digital image data corresponding to areas outside of the region of interest. In the alternative, the region of interest can be reconstructed with a higher fidelity than areas outside of the region of interest.
• the threshold or path where region of interest coding begins can be determined at the beginning of the sorting pass on and overall image or in the middle of the sorting pass, as well as in the beginning or middle of a refinement pass, or in the beginning of the entire coding process. If it is determined in the beginning of the entire coding process, this can be done in an off-line manner.
• An alternative embodiment of a system according to the present invention would be one wherein the selection of the region of interest is 14 performed based upon a partial reconstructed image which is received by the receiver after transmission from the transmitting means has begun. Based upon the partial reconstructed image, a user on the receiving end can select a region of interest, and the receiver then transmits data to the transmitting computer which identifies the selected region of interest. The transmitting computer then modifies the sorting of the digital image data based upon the selected region of interest. The digital image data corresponding to the region of interest is sorted and prioritized to have a higher priority than digital image data corresponding to areas outside of the region of interest.
• the modified sorted and prioritized data is then transmitted to the receiver, and the region of interest is transmitted with a higher priority than areas outside of the region of interest.
• the specific configuration of the computer elements to create means for performing the function specified above is within the purview of a person of skill in the art based upon the information contained in the specification.
• FIG. 10 is a block diagram which illustrates a series of elements which implement the invention wherein ROI selection is performed on the encoding side.
• Input means or input device 110 is used for inputting digital image data into a computer or data handling apparatus.
• a display means or device 111 displays the digital image data.
• Selecting device 112 is connected to the display device, and is used to select a region of an image represented by the digital image data.
• Sorting and prioritizing device 113 is connected to selecting device 112, and sorts and prioritizes the digital image data according to at least two priority categories. The selected region of interest data is given a higher priority than digital image data corresponding to areas outside of the region of interest.
• Transmitting device 114 transmits the sorted and prioritized data to a remote location, with the remote location being a mass storage device, a network such as an internet or intranet, wide area network, local area network, etc.
• the transmitted data is received by receiving device 115, wherein the transmitted digital image data is reconstructed by reconstructing means 116 having decoding means 117, 15 wherein the region of interest is reconstructed at a faster rate and/or with a higher fidelity than digital image data corresponding to areas outside of the region of interest.
• FIG 11 is a block diagram which illustrates region of interest selection in an on-line manner.
• Input means or input device 121 inputs digital image data to a computer or other image data handling apparatus.
• the digital image can then optionally be displayed on display means 122, or, alternatively, may be communicated directly to sorting means or sorting device 123.
• the sorting device sorts the digital image data according to a mathematical sorting protocol, with the digital image data being sorted and prioritized according to a predetermined prioritization formula.
• Transmitting means or transmitting device 124 transmits the sorted data, and the sorting means repeats a sorting of the digital image data and the transmitting means repeats a transmission of the data.
• the data is received on a receiving device 125, which has display device 126 connected thereupon.
• the display device displays the transmitted data as a partial reconstructed image during the transmission.
• a region of interest selecting means 127 is connected to receiving means 125, for selecting a region of interest based upon the partial reconstructed image.
• a region of interest transmitting device or means 128 transmits data corresponding to the selected region of interest to the sorting device 123.
• the sorting device modifies the sorting of the digital image data based upon the data corresponding to the selected region of interest.
• the digital image data corresponding to the selected region of interest is sorted and prioritized by the sorting device to have a higher priority than digital image data corresponding to areas outside of the selected region of interest.
• the present invention takes the form of a computer program embodied on a computer readable medium, with the computer readable medium including floppy disks, mass storage devices such as hard drives, DRAM, CD- 16
• the computer program controls a general purpose computer to perform the method steps noted above.
• the invention is discussed above as being implemented on a transmitting computer or device and the data is sent to a receiver or a decoding device.
• the invention can include configurations wherein the encoding is performed on a computer, wherein encoded image data is transmitted onto the internet for internet browsing, and decoding occurs at another computer retrieving information from the internet.
• the encoder and the decoder can also be disposed on a local area network (LAN) or wide area network (WAN), intranet, or can occur between a computer and a mass storage device.
• Applications could therefore include virtually any applications where image data transfer or storage is necessary, including telemedicine and general image archival and retrieval.
• the region of interest coding method and apparatus according to the invention solves bottleneck problems which occur in these applications.

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• 1998
  • 1998-03-20 JP JP2000538314A patent/JP3597780B2/ja not_active Expired - Lifetime
  • 1998-03-20 KR KR1020007010414A patent/KR100550105B1/ko not_active IP Right Cessation
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