A Novel Method for Image and Video Compression Based on Two-Level DCT with Hexadata Coding

Abstract

In this paper a novel method for 2D image compression is proposed and demonstrated through high quality reconstruction with compression ratios up to 99%. The proposed novel algorithm is based on a two-level discrete cosine transform (DCT) followed by Hexadata coding and arithmetic coding at compression stage. The novel method consists of four main steps: (1) a two-level DCT is applied to an image to reinforce the low frequency coefficients and increase the number of high frequency coefficients to facilitate the compression process; (2) the Hexadata coding algorithm is applied to each high frequency matrix separately through five different keys to reduce each matrix to 1/6 of their original size; (3) build a probability table of original high-frequency data required in the decoding step; and (4) apply arithmetic coding to compress each of the outputs of steps (2) and (3). At decompression stage, arithmetic decoding and a fast matching search algorithm (FMS-Algorithm) decodes the high frequency coefficients of step (2) using the probability table of step (3). Finally, two level inverse DCT is applied to decode the high frequency coefficients to reconstruct the image. The technique is demonstrated on still images including video streaming from YouTube. The results show that the proposed method yields high compression ratios up to 99% with better perceptual quality of reconstructed images as compared with the popular JPEG method.