An image deblocking method based on pre-classified sparse representation

Block-based Discrete Cosine Transform (BDCT) image compression method inevitably produces annoying blocking artifacts in the case of low-bit-rate compression, as each block is transformed and quantized independently. Blocking artifacts not only seriously affect the subjective image quality, but also affect the performance of automatic analysis. In this paper, we propose a pre-classified sparse representation based deblocking method. We combine the human visual sensitivity based classification and the sparse representation method together. For different contents, the reconstruction threshold can been adaptively adjusted. Experimental results show that the proposed method can improve the deblocking quality of the compressed images effectively.