%0 Journal Article %T Deblocking Joint Photographic Experts Group Compressed Images via Self-learning Sparse Representation %J International Journal of Engineering %I Materials and Energy Research Center %Z 1025-2495 %A Hassanpour, Hamid %A Asadi, Sekineh %D 2016 %\ 12/01/2016 %V 29 %N 12 %P 1684-1690 %! Deblocking Joint Photographic Experts Group Compressed Images via Self-learning Sparse Representation %K Image Compression %K blocking effect %K Post %K processing %K Sparse representation %K low bit %K rate %R %X 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. %U https://www.ije.ir/article_72842_e6a90ec437849e8c4d815b7237b200e0.pdf