Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/23623
Title: Neural network modelled POCS method for removing blocking effect
Authors: Hong, SW
Chan, YH 
Siu, WC 
Issue Date: 1995
Publisher: IEEE
Source: IEEE International Conference on Neural Networks - Conference Proceedings, 1995, v. 3, p. 1422-1425 How to cite?
Abstract: This paper proposes a new method for real-time realization of the blocking effect elimination. This is achieved by training a feed-forward single-layer neural network (FFSLN) to restore block boundaries of JPEG encoded images. The reconstructed image of the iterative projection onto convex sets (POCS) method instead of the original image is chosen as the target output in this proposed method. Computer simulation result demonstrates the superiority of the new method as compared with the original POCS iterative recovery method.
Description: Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6), Perth, Aust, 27 November-1 December 1995
URI: http://hdl.handle.net/10397/23623
Appears in Collections:Conference Paper

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