Title: | An HVS-Directed neural-network-based image resolution enhancement scheme for image resizing |
Authors: | Lin, Chin-Teng Fan, Kang-Wei Pu, Her-Chang Lu, Shih-Mao Liang, Sheng-Fu 交大名義發表 生物科技學系 資訊工程學系 電控工程研究所 National Chiao Tung University Department of Biological Science and Technology Department of Computer Science Institute of Electrical and Control Engineering |
Keywords: | fuzzy decision system;human visual system;image interpolation;neural network;resolution enhancement |
Issue Date: | 1-Aug-2007 |
Abstract: | In this paper, a novel human visual system (HVS)directed neural-network-based adaptive interpolation scheme for natural image is proposed. A fuzzy decision system built from the characteristics of the HVS is proposed to classify pixels of the input image into human perception nonsensitive class and sensitive class. Bilinear interpolation is used to interpolate the nonsensitive regions and a neural network is proposed to interpolate the sensitive regions along edge directions. High-resolution digital images along with supervised learning algorithms are used to automatically train the proposed neural network. Simulation results demonstrate that the proposed new resolution enhancement algorithm can produce a higher visual quality for the interpolated image than the conventional interpolation methods. |
URI: | http://dx.doi.org/10.1109/TFUZZ.2006.889875 http://hdl.handle.net/11536/10505 |
ISSN: | 1063-6706 |
DOI: | 10.1109/TFUZZ.2006.889875 |
Journal: | IEEE TRANSACTIONS ON FUZZY SYSTEMS |
Volume: | 15 |
Issue: | 4 |
Begin Page: | 605 |
End Page: | 615 |
Appears in Collections: | Articles |
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