An Overview and Performance Evaluation of Classification-Based Least Squares Trained Filters

Shao, Ling, Zhang, Hui and de Haan, Gerard (2008) An Overview and Performance Evaluation of Classification-Based Least Squares Trained Filters. IEEE Transactions on Image Processing, 17 (10). pp. 1772-1782. ISSN 1057-7149

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Official URL: http://dx.doi.org/10.1109/TIP.2008.2002162

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.

Item Type: Article
Uncontrolled Keywords: Adaptive filters, classification, integrated processing, least squares optimization, performance evaluation, trained filters, video enhancement
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer Science and Digital Technologies
Depositing User: Paul Burns
Date Deposited: 15 Jun 2015 12:09
Last Modified: 03 Nov 2016 11:42
URI: http://nrl.northumbria.ac.uk/id/eprint/22895

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