Restoration of block-transform compressed images via homotopic regularized sparse reconstruction
Jeffrey Glaister, Shahid Abbas Haider, Alexander K.C. Wong, David A. Clausi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2015
Block-transform lossy image compression is the most widely-used approach for compressing and storing images or video. A novel algorithm to restore highly compressed images with greater image quality is proposed. Since many block-transform coefficients are reduced to zero after quantization, the compressed image restoration problem can be treated as a sparse reconstruction problem where the original image is reconstructed based on sparse, degraded measurements in the form of highly quantized block-transform coefficients. The sparse reconstruction problem is solved by minimizing a homotopic regularized function, subject to data fidelity in the block-transform domain. Experimental results using compressed natural images at di erent levels of compression show improved performance by using the proposed algorithm compared to other methods.