VLSI Implementation of a Cost-Efficient Near-Lossless CFA Image Compressor for Wireless Capsule Endoscopy

Abstract

In this paper, a novel near-lossless color filter array (CFA) image compression algorithm based on JPEG-LS is proposed for VLSI implementation. It consists of a pixel restoration, a prediction, a run mode, and entropy coding modules. According to the information of the previous research, a context table and row memory consumed more than 81% hardware cost in a JPEG-LS encoder design. Hence, in this paper, a novel context-free and near-lossless image compression algorithm is presented. Since removing the context model causes decreasing of the compression performance, a novel prediction, run mode, and modified Golomb-Rice coding techniques were used to improve the compression efficiency. The VLSI architecture of the proposed image compressor consists of a register bank, a pixel restoration module, a predictor, a run mode module, and an entropy encoder. A pipeline technique was used to improve the performance of this. It contains only 10.9k gate count, and the core area is 30625 μm 2 , synthesized by using a 90-nm CMOS process. Compared with the previous JPEG-LS designs, this paper reduces the gate counts by 44.1% and 41.7%, respectively, for five standard and eight endoscopy testing images in CFA format. It also improves the average PSNR values by 0.96 and 0.43 dB, respectively, for the same test images.