Perceptual Image Coding Based on a Maximum of Minimal Structural Similarity Criterion
Zhou Wang, Qiang Li, Xinli Shang · 2007
Perceptual image coding algorithms typically impose perceptual modeling in a preprocessing stage. A perceptual normalization model is often used to transform the original image signal into a perceptually uniform space, in which all the transform coefficients have equal perceptual importance. Standard coding schemes are then applied uniformly to all coefficients. Here we use a different approach, in which we iteratively reallocates the available bits over the image space based on amaximumofminimalstructuralsimilaritycriterion. We demonstrate the proposed method by incorporating it with the bitplane coding scheme in the set partitioning in hierarchical trees algorithm.