Multiscale recurrent patterns applied to stereo image coding

For the compression of stereo images, several techniques employing the concept of disparity compensation have been developed. In this paper, we present a new method for stereo-image compression which is based on a different paradigm. It relies on approximate matching of multiscale recurrent patterns, which is an extension of ordinary pattern matching, where an image block is represented using dilated, contracted, displaced, and deformed versions of blocks already processed. To achieve this, the input image is segmented into variable-sized blocks. Each segment is represented by an element in a dictionary. The segmentation is performed according to a rate × distortion criterion, and the dictionary is updated with the concatenation, contraction, expansion, displacement, and deformation of previously coded elements. Unlike most other methods, in this approach the disparity map is not transmitted. That is, the generation of the error images, as well as their coding and transmission, is not necessary. In brief, the proposed method presents high-quality results at the decoder end, compared to other coding methods for stereo images that transmit the disparity map.