A Novel ASIC Implementation of Two-Dimensional Image Compression Using Improved B.G. Lee Algorithm

Abstract

A 2D Discrete Cosine Transform and Inverse Discrete Cosine Transform using the B.G. Lee algorithm, incorporating a signed error-tolerant adder for additions, and a signed low-power fixed-point multiplier to perform multiplications are proposed and designed in this research. A novel Application Specific Integrated Circuit hardware implementation is used for the 2D DCT/IDCT computation of each 8 × 8 image block by optimizing the input data using the concepts of pipelining. An enhanced speed in processing and optimized arithmetic computations was observed due to the eight-stage pipeline architecture. The 2D DCT/IDCT of each 8 × 8 image segment can be quickly processed in 34 clock cycles with a substantially reduced level of circuit complexity. The B.G. Lee algorithm has been implemented using signed error-tolerant adders, signed fixed-point multipliers, and shifters, reducing computational complexity, power, and area. The Cadence Genus tool synthesized the proposed architecture with gpdk-90 nm and gpdk-45 nm technology libraries. The proposed method showed a significant reduction of 31.01%, 12.17%, and 21.11% in power, area, and PDP in comparison to the existing image compression architectures. An improved PSNR of the reconstructed image was also achieved compared to existing designs.