A Training-Based Method for Reducing Ringing Artifact in BDCT-Encoded Images

dc.contributor.authorWang, Guangyuen_US
dc.contributor.authorWong, Tien-Tsinen_US
dc.contributor.authorHeng, Pheng-Annen_US
dc.contributor.editorN. Correia and J. Jorge and T. Chambel and Z. Panen_US
dc.date.accessioned2014-01-26T16:16:43Z
dc.date.available2014-01-26T16:16:43Z
dc.date.issued2004en_US
dc.description.abstractThe quantization procedure of block-based discrete cosine transform (BDCT) compression (such as JPEG) introduces annoying visual artifact. In this paper, we propose a novel training-based method to reduce the ringing artifact in BDCT-encoded high-contrast images (images with large smooth color areas and strong edges/outlines). Our main focus is on the removal of ringing artifact that is seldom addressed by existing methods. In the proposed method, the contaminated image is modeled as a Markov random field (MRF). We learn the behavior of contamination by extracting massive number of artifact patterns from a training set. To organize the extracted artifact patterns, we use the tree-structured vector quantization (TSVQ). Instead of post-filtering the input contaminated image, we synthesize an artifact-reduced image. We show that substantial improvement (both statistical and visual) is achieved using the proposed method. Moreover, since our method is non-iterative, it can remove artifact within a very short period of time.en_US
dc.description.seriesinformationEurographics Multimedia Workshopen_US
dc.identifier.isbn3-905673-17-7en_US
dc.identifier.issn1812-7118en_US
dc.identifier.urihttps://doi.org/10.2312/EGMM/MM04/105-113en_US
dc.publisherThe Eurographics Associationen_US
dc.titleA Training-Based Method for Reducing Ringing Artifact in BDCT-Encoded Imagesen_US
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