Notice of Violation of IEEE Publication Principles - A DCT approximation with low complexity for image compression

Abstract

This paper introduces an orthogonal approximation for the 8 point Discrete Cosine Transform (DCT). The proposed transformation matrix contains only ones and zeros. Bit shift operations and multiplication operations are absent. The approximate transform of DCT is obtained to meet the low complexity requirements. The implied transformation and approximation are orthogonal and are based on polar decomposition methods. The low complexity introduced in DCT reduces power consumption. The proposed image compression algorithm is comprehended using Matlab code. The proposed algorithm is less complex than Signed Discrete Cosine Transform (SDCT) and it requires two additional operations when compared to Bouguezel-Ahmed-Swamy (BAS) series of algorithms.

Comparative Study on MATLAB based JPEG Image Size Reduction Using Discrete Cosine Transform and Shearlet Transform for Mammogram Images with Potential Hospital Data Storage Applications

“…In this study we observed that DCT transform seems to have a better compression ratio than (Saraswathy et al, 2013). In another research, authors have performed image compression using spectrum PSF (Point spread function) determined using spectrum (Kumar et al, 2017); (Chen, 2007).…”

“…Few authors have developed some simple functions to compete with DCT and to compare images (Gupta, M., & Garg, A. K., n.d.); (Barbhuiya et al, 2014). Very recently, image compression based on ROI detection and shearlet transform were experimented and reported their feasibility as a compression tool (Saraswathy et al, 2013); (Katharotiya et al, 2011). Authors also have performed image compression using DCT and wavelet transforms by selecting proper threshold methods along with PSNR (Telagarapu et al, 2011); (Yuen & Wong, 2011).…”