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Adaptive Blocking Artifacts Reduction in Block-Coded Images Using Block Classification and MLP  

Kwon, Kee-Koo (School of Electrical Engineering and Computer Science, Kyunpook National University)
Kim, Byung-Ju (School of Electrical Engineering and Computer Science, Kyunpook National University)
Lee, Suk-Hwan (School of Electrical Engineering and Computer Science, Kyunpook National University)
Lee, Jong-Won (School of Electrical Engineering and Computer Science, Kyunpook National University)
Kwon, Seong-Geun (School of Electrical Engineering and Computer Science, Kyunpook National University)
Lee, Kuhn-Il (School of Electrical Engineering and Computer Science, Kyunpook National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.39, no.4, 2002 , pp. 399-407 More about this Journal
Abstract
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.
Keywords
Blockin artifacts; block classification; multi-layer perceptron; error back-propagation learning algorithm;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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