Composite video artifact removal by nonlinear bilateral filtering

Kim, Sunghee; Hong, Kimin

doi:10.1117/12.631409

Cited by 3 publications

(2 citation statements)

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“…NN filters are trained with four video sequences (Mobile, Football, Children, and Foreman sequences) having various characteristics. For performance comparison of the proposed algorithm, a bilateral filtering method is simulated [4].…”

Section: Resultsmentioning

confidence: 99%

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Adaptive video enhancement using neural network

Lee

Park

Kim

2009

2009 Digest of Technical Papers International Conference on Consumer Electronics

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This paper proposes an adaptive video enhancement method using neural network (NN). Inaccurate separation of the composite video signal produces cross-luma artifacts such as dot crawls and blurs edges of an image. Even digital televisions suffer from these artifacts because high definition contents are based on old technology. In order to correct old artifacts we propose two types of NN filtering. Each decoded video frame is segmented into regions of artifacts and enhanced by proposed NN filters. Proposed NN filters adaptively enhance video frame based on the region classification index of a pixel. Experiments using a number of video sequences verify the effectiveness of the proposed algorithm.

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Section: Resultsmentioning

confidence: 99%

“…A large number of methods have been proposed for reducing analog video artifacts based on post-processing. Block matching temporal filtering [3] and bilateral filtering [4] methods were presented to reduce dot-crawl artifacts. Also, neural network (NN) filtering was used to restore the blurred edges [5].…”

Section: Introductionmentioning

confidence: 99%