Picture Quality Improvement in Low Bit Rate Video Coding Using Block Boundary Classification and Simple Adaptive Filter

Abstract

In this paper, we propose a novel post-filtering algorithm with low computational complexity that improves the visual quality of block-based coded images using block boundary classification and simple adaptive filter (SAF). In this algorithm, each block boundary is classified into smooth or complex sub-region, and the existence of blocking artifacts is determined using blocky strength for smooth-smooth sub-regions. Simple adaptive filtering is processed adaptively in each block boundary. That is, a nonlinear 1-D 8-tap filter is applied to smooth-smooth sub-regions with blocking artifacts, and for smooth-complex or complex-smooth sub-regions, a nonlinear 1-D variant filter is applied to block boundary pixels so as to reduce the blocking and ringing artifacts. And for complex-complex sub-regions, a nonlinear 1-D 2-tap filter is only applied to adjust two block boundary pixels so as to preserve the image details. Experimental results show that the proposed algorithm produced better results than those of the conventional algorithms both subjective and objective viewpoints.