Though the sparse representation has demonstrated to be a very effective tool to de-noise the images with low levels of noise, it usually losses the power to well preserve structural features in images with high levels of noise. In this paper, we propose an improved de-noising method for images with low signal- to noise ratio. Specifically, the proposed method takes the histogram structural similarity (HSSIM) as similarity factor to replace the reconstruction error as the new fidelity term, and finds the most appropriate sparse coefficients by using the modified orthogonal matching pursuit (OM...
