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Status已发表Published
TitleAn overview and performance evaluation of classification-based least squares trained filters
Creator
Date Issued2008
Source PublicationIEEE Transactions on Image Processing
ISSN1057-7149
Volume17
Issue10
Pages1772-1782
Abstract

An overview of the classification-based least squares trained filters on picture quality improvement algorithms is presented. For each algorithm, the training process is unique and individually selected classification methods are proposed. Objective evaluation is carried out to single out the optimal classification method for each application. To optimize combined video processing algorithms, integrated solutions are benchmarked against cascaded filters. The results show that the performance of integrated designs is superior to that of cascaded filters when the combined applications have conflicting demands in the frequency spectrum. © 2008 IEEE.

KeywordAdaptive filters Classification Integrated processing Least squares optimization Performance evaluation Trained filters Video enhancement
DOI10.1109/TIP.2008.2002162
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial IntelligenceEngineering, Electrical & Electronic
WOS IDWOS:000259372100003
Scopus ID2-s2.0-52649097525
Citation statistics
Cited Times:71[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeReview
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/6656
CollectionFaculty of Science and Technology
Affiliation
1.Video Processing and Analysis Group,Philips Research Laboratories,High Tech Campus 36,Eindhoven 5656 AE,Netherlands
2.Department of Computer Science and Technology,United International College,Zhuhai,China
Recommended Citation
GB/T 7714
Shao, Ling,Zhang, Hui,de Haan, Gerard. An overview and performance evaluation of classification-based least squares trained filters. 2008.
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