Foveation image coding with fuzzy-based joint parameter selection

This paper presents a novel method of the foveation image coding based on the fuzzy-based joint parameter selection. Our objective is to maximize foveated wavelet image quality index (FWQI) of the reconstructed image. With the foveated visual sensitivity model, image regions are first prioritized. The image regions close to foveation points have higher priorities than those far away from the foveation points. The discrete wavelet transform (DWT) is utilized to transform the considering image to the wavelet domain. The wavelet coefficients from different image regions are weighted using the foveated visual sensitivity model and then scaled down before entropy encoding. To achieve the objective, we use a fuzzy logic system and an iterative search to select image coding parameters under the bit budget constraint. The coding parameters consist of a number of weighted wavelet coefficients in the list significant pixel (LSP) of the SPIHT codec [A. Said, W.A. Pearlman, A new, fast, and efficient image codec based on set partitioning in hierarchical trees, IEEE Trans. Circuits Syst. Video Technol. 6 (3) (1996) 243–250], represented as NLSP, and a scaling down factor (QP). There are two inputs and one output in the proposed fuzzy logic system. The inputs are NLSP and targeted bit per pixel used to encode an image. The output is an interval of QP. The QP value corresponding to the input NLSP giving the highest FWQI is selected from the derived interval. We iteratively search for the values of NLSP and QP providing the highest FWQI. Then, the SPIHT codec is used to generate a scalable bitstream of the discrete wavelet coefficients with the optimal pair of NLSP and QP. The sub-optimal search algorithm to compute both NLSP and QP with low complexity is also proposed. Our simulation results show that the proposed scheme provides a better reconstructed image quality comparing to previous work in both objective and subjective qualities.