Adaptive Blocking Artifacts Reduction in Block-Coded Images Using Block Classification and MLP
Kee-Koo Kwon, Byung-Ju Kim, Suk‐Hwan Lee, Jong‐Won Lee, Seong-Geun Kwon, Kuhn-Il Lee · Journal of the Institute of Electronics Engineers of Korea · 2002
In this paper, a novel algorithm is proposed to reduce the blocking artifacts of block-based coded images by using block classification and MLP. In the proposed algorithm, we classify the block into four classes based on a characteristic of DCT coefficients. And then, according to the class information of neighborhood block, adaptive neural network filter is performed in horizontal and vertical block boundary. That is, for smooth region, horizontal edge region, vertical edge region, and complex region, we use a different two-layer neural network filter to remove blocking artifacts. Experimental results show that the proposed algorithm gives better results than the conventional algorithms both subjectively and objectively.