Quantum-dot Cellular Automata Based Lossless CFA Image Compression Using Improved and Extended Golomb-rice Entropy Coder

Abstract

This article presents an efficient hardware architecture of lossless image compression mechanism using colour filter array (CFA) for wireless camera networks. Recently, Quantum-dot cellular automata (QCA) technology has been widely using in the field of VLSI, thus the proposed compressor is developed using QCA technology to mitigate the area, and power as compared to standard CMOS technology. In addition, an improved and extended Golomb-Rice entropy coder (IEGREC) is proposed to reduce the memory requirement, and computational complexity. The IEGREC approach eliminates the requirement of context module, which is a major component in lossless image compressor architectures and its memory to lessen the hardware resource utilization. Further, to maintain the pixel connectivity and higher compression ratio (CR), the proposed architecture utilizes the adaptive Golomb-Rice (GR) parameter prediction and control module. Finally, packer module is used to maintain the flow of output compressed bit stream. The extensive simulation results show that proposed QCA-IEGREC method performs superior as compared to state-of-art approaches in terms of lesser area as 3700 gate count, and reduced power of 1.02 mW, and even image quality statistics such as 18.78dB of peak signal-to-noise ratio (PSNR), 152.3 of figure-ofmerit (FOM), and 29.3 of CR.