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Proceedings Paper

Color image super-resolution reconstruction based on POCS with edge preserving
Author(s): Rui Wang; Ying Liang; Yu Liang
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Paper Abstract

A color image super-resolution (SR) reconstruction based on an improved Projection onto Convex Sets (POCS) in YCbCr space is proposed. Compared with other methods, the POCS method is more intuitive and generally simple to implement. However, conventional POCS algorithm is strict to the accuracy of movement estimation and it is not conducive to the resumption of the edge and details of images. Addressed to these two problems, we on one hand improve the LOG operator to detect edges with the directions of ±0°, ±45°, ±90°, ±135° in order to inhibit the edge degradation. Then, by using the edge information, we proposed a self-adaptive edge-directed interpolation and a modified adaptive direction PSF to construct a reference image as well as to reduce the edge oscillation when revising the reference respectively. On the other hand, instead of block-matching, the Speeded up Robust Feature (SURF) matching algorithm, which can accurately extract the feature points with invariant to affine transform, rotation, scale, illumination changes, are utilized to improve the robustness and real-time in motion estimation. The performance of the proposed approach has been tested on several images and the obtained results demonstrate that it is competitive or rather better in quality and efficiency in comparison with the traditional POCS.

Paper Details

Date Published: 8 October 2015
PDF: 6 pages
Proc. SPIE 9675, AOPC 2015: Image Processing and Analysis, 96750X (8 October 2015); doi: 10.1117/12.2199058
Show Author Affiliations
Rui Wang, Beihang Univ. (China)
Ying Liang, Beihang Univ. (China)
Yu Liang, Beihang Univ. (China)

Published in SPIE Proceedings Vol. 9675:
AOPC 2015: Image Processing and Analysis
Chunhua Shen; Weiping Yang; Honghai Liu, Editor(s)

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