Perceptual Image Coding Based on a Maximum of Minimal Structural Similarity Criterion
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 a maximum of minimal structural similarity criterion. We demonstrate the proposed method by incorporating it with the bitplane coding scheme in the set partitioning in hierarchical trees algorithm.