Lifting based 2d-Discrete Wavelet Transform for Image Compression based on Residue Number System

Abstract

The high-performance of image compression is needed greater as digital image finds its way into many areas of everyday life. In order to transmit and store digital images, the images must be compressed; otherwise, each image would require a large amount of memory. JPEG 2000 which is one of the bestimage compression standardis used. Unlike the discrete cosine transform, DWT has higher compression ratios, no blocking artifacts and good localization in time and frequency domain, inherent scaling and higher flexibility. Owing to such inherent advantages of DWT, two-dimensional (2D) bi-orthogonal reversible/irreversible DWT is adopted in JPEG2000 still image compression standard. In the proposed work the 2-D Discrete Wavelet Transform (DWT), using 9/7 filter with lifting scheme is designed. Lower computational complexity and reduced memory requirement are the advantages of lifting scheme. Predictor and updater are the two coefficients used in the DWT decomposition process with lifting scheme. In the 2D DWT lifting based structure multipliers are the more power consumed computational blocks. So in order to reduce the power and to increase the speed of the system, the array multipliers are replaced by Residue Number System(RNS) multiplier and adders by RNS adder. Thus the entire lifting structure is designed to operate with RNS. So, the complexity in computation and power consumption are reduced. Using Synopsystool reports of design vision are obtained to verify power and area of both array multiplier lifting structure and RNS lifting structure.