Repairing imperfect video enhancement algorithms using classification-based trained filters

Ling Shao, Hui Zhang, Liang Wang, Lijun Wang

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)


There are numerous video processing algorithms and modules available. When the algorithms are not optimally tuned, undesired results may happen in the processed video signals, e.g. blurring, overshoots/downshoots, loss of details and aliasing. When the video processing modules are fixed, e.g. when the modules are implemented in hardware/chips, it is highly desirable to repair those unpleasant effects caused by certain imperfect algorithms. In this paper, we propose a solution based on classification and least squares trained filters to repair/patch low-quality video processing modules at the back end of a video chain. Extensive experiments show that the repairing method can significantly improve the video quality without modifying the original processing modules.
Original languageEnglish
Pages (from-to)307-313
JournalSignal, Image and Video Processing
Issue number3
Publication statusPublished - 13 Jan 2011


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