An approach to image compression using R-D optimal OMP selection

Transform-based coding is a technique that is widely used in image and video compression, where compression is achieved via decomposing each component block or patch over a complete dictionary known to provide compaction. Recently, there has been a growing interest in using basis selection algorithms for signal approximation and compression. Signal approximation using a linear combination of basis functions from an over-complete dictionary has proven to be an NP-hard problem. To solve this problem, Orthogonal Matching Pursuit (OMP) algorithm is often used to select dictionary elements and their coefficients. Based on its iterative nature, we propose a Rate-Distortion Optimization (RDO) method to select the number of nonzero coefficients assuming that a sparsity constraint is given. Experimental results demonstrate a very good improvement by our proposed method over conventional DCT based scheme.