An experimental analysis of an advanced OMP algorithm for image compression in an OSCC approach

Image compression has been a widely researched field for decades. Several methods are available and standards exist that provide high compression ratios for a given subjective quality. From pervious analysis the DCT and wavelet based compression methods suffer from blocking and ringing artifacts and also they are unable to capture the directional information. So, in this context an investigation has been made to this paper by using sparse coding method by an advanced orthogonal matching pursuit (OMP). In this proposed framework, the conventional DCT can be replaced by a set of trained dictionaries. For dictionary construction we have used a combination of DCT and Gabor basis and to encode the trained dictionary elements we have employed advanced OMP algorithm. Experimental results demonstrate that the proposed method provides gains in rate distortion (RD) performance and improvements in perceptual quality.