Image blocking artifact suppression by the modified fuzzy rule based filter

In this paper, we propose the modified fuzzy rule-based (MFRB) filter for JPEG-encoded image blocking noise removal. The proposed filter generalizes the FRB filter, which is a weighted average of the center pixel and its neighboring pixels in a working window. The weighting coefficients of the MFRB filter depend on the gray level difference, the spatial distance and orientation, and the variance of the pixels in the window. By the least mean square (LMS) learning over representative JPEG-encoded images, the best membership function, i.e., the weight coefficients, of the MFRB filter for blocking noise suppression can be determined. By the simulation results, our proposed scheme has demonstrated the effectiveness and robustness in blocking noise removal. Compared to several post-filtering approaches, our MFRB filter has produced the best SNR improvement among the resultant images. This objective superiority is also confirmed visually by the sharper and more pleasing image obtained.