Abstract: images are used in many applications including autonomous vehicle navigation, geoscience, and machine vision. The storage and transmission of the stereo images involve large amounts of data. Therefore, efficient coding techniques are required to encode the two correlated stereo image pairs with low bit rates. This paper presents two techniques to compress stereo image data. The proposed schemes are based on subband coding and disparity compensation (DC). DC, which is similar to motion compensation, exploits the redundancy that exists between two stereo images. In the first method, the two images are decomposed into four subbands using two-tap filters. The lowest band of the left image is coded using block DPCM and DC is applied to code the lowest band of the right image. The high bands are directly quantized and PCM coded. The coding is adaptive in the sense that different quantizers are selected based on the activity of each block. In the second method, disparity compensated interpolative predictive coding, DC is applied to the original images and proceeds in a different way. To find the differential signals, the pixels in each block of the right image are divided into two groups, P1 and P2. P1 pixels are predicted by the corresponding pixels in its matching block and P2 pixels are predicted interpolatively by the decoded P1 pixels. Finally, a method for the lossless coding of the disparity information is presented. The proposed lossless scheme reduces the overhead information and the search efforts. !10
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