Morphological wavelet-based stereo image coders

In this paper, we propose a family of novel stereoscopic image coders based on morphological coding and a block-based disparity compensation algorithm. The proposed schemes employ discrete wavelet transform decomposition and a morphological coder that lowers total entropy by exploiting the intra-band and inter-band statistical properties of the wavelet coefficients. This ensures high coding efficiency, embedded bit streams, fast execution, and simple implementation. Disparity compensation procedure is implemented on blocks of fixed or variable size employing the block-matching algorithm. The blocks of variable size are formed as a result of Right image’s quad-tree decomposition with a simplified rate-distortion criterion. This technique adapts block size to regions of almost constant binocular disparity in contradiction with fixed block size based disparity estimation that divides these regions into smaller blocks, thus requiring more disparity vectors. The Left and the resulting predictive error images are subsequently transformed, quantized, and coded. The wavelet nature of the algorithm and the proposed disparity compensation provide reconstructed images without blocking artifacts and fewer annoying ringing effects. The extensive experimental evaluation shows that the proposed coders demonstrate very good performance as far as PSNR measures and visual quality are concerned, as well as low complexity.