Status | 已发表Published |
Title | An overview and performance evaluation of classification-based least squares trained filters |
Creator | |
Date Issued | 2008 |
Source Publication | IEEE Transactions on Image Processing |
ISSN | 1057-7149 |
Volume | 17 |
Issue | 10 |
Pages | 1772-1782 |
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. |
Keyword | Adaptive filters Classification Integrated processing Least squares optimization Performance evaluation Trained filters Video enhancement |
DOI | 10.1109/TIP.2008.2002162 |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Computer Science ; Engineering |
WOS Subject | Computer Science, Artificial IntelligenceEngineering, Electrical & Electronic |
WOS ID | WOS:000259372100003 |
Scopus ID | 2-s2.0-52649097525 |
Citation statistics | |
Document Type | Review |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/6656 |
Collection | Faculty 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. |
Files in This Item: | There are no files associated with this item. |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment