Deblocking Joint Photographic Experts Group Compressed Images via Self-learning Sparse Representation

Authors

Faculty of Engineering, University of Mazandaran

Abstract

JPEG is one of the most widely used image compression method, but it causes annoying blocking artifacts at low bit-rates. Sparse representation is an efficient technique which can solve many inverse problems in image processing applications such as denoising and deblocking. In this paper, a post-processing method is proposed for reducing JPEG blocking effects via sparse representation. In this method, a dictionary is learned via the single input blocky image using K-SVD. There is no need for any prior knowledge about the blocking artifacts. Experimental results on various images demonstrate that the proposed post-processing method can efficiently alleviate the blocking effects at low bit-rates and outperforms the existing methods.

Keywords