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Frontiers of Computer Science

ISSN 2095-2228

ISSN 2095-2236(Online)

CN 10-1014/TP

Postal Subscription Code 80-970

2018 Impact Factor: 1.129

Front. Comput. Sci.    2015, Vol. 9 Issue (5) : 703-712    https://doi.org/10.1007/s11704-015-4179-x
RESEARCH ARTICLE
A novel adaptive image zooming scheme via weighted least-squares estimation
Xuexia ZHONG1,Guorui FENG2,*(),Jian WANG1,3,4,Wenfei WANG1,Wen SI5
1. Cyber Physical System Research and Development Center, The Third Research Institute of Ministry of Public Security, Shanghai 201204, China
2. School of Communication and Information Engineering, Shanghai University, Shanghai 200444, China
3. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
4. Shanghai Chenrui Information Technology Company, Shanghai 201204, China
5. College of Information and Computer Science, Shanghai Business School, Shanghai 201400, China
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Abstract

A critical issue in image interpolation is preserving edge detail and texture information in images when zooming. In this paper, we propose a novel adaptive image zooming algorithm using weighted least-square estimation that can achieve arbitrary integer-ratio zoom (WLS-AIZ) For a given zooming ratio n, every pixel in a low-resolution (LR) image is associated with an n × n block of high-resolution (HR) pixels in the HR image. In WLS-AIZ, the LR image is interpolated using the bilinear method in advance. Model parameters of every n × n block are worked out throughweighted least-square estimation. Subsequently, each pixel in the n × n block is substituted by a combination of its eight neighboring HR pixels using estimated parameters. Finally, a refinement strategy is adopted to obtain the ultimate HR pixel values. The proposed algorithm has significant adaptability to local image structure. Extensive experiments comparingWLS-AIZ with other state of the art image zooming methods demonstrate the superiority of WLS-AIZ. In terms of peak signal to noise ratio (PSNR), structural similarity index (SSIM) and feature similarity index (FSIM), WLS-AIZ produces better results than all other image integer-ratio zoom algorithms.

Keywords adaptive interpolation      refinement strategy      weighted least-squares estimation      arbitrary integer an WLS-AIZ scheme     
Corresponding Author(s): Guorui FENG   
Just Accepted Date: 16 January 2015   Issue Date: 24 September 2015
 Cite this article:   
Xuexia ZHONG,Guorui FENG,Jian WANG, et al. A novel adaptive image zooming scheme via weighted least-squares estimation[J]. Front. Comput. Sci., 2015, 9(5): 703-712.
 URL:  
https://academic.hep.com.cn/fcs/EN/10.1007/s11704-015-4179-x
https://academic.hep.com.cn/fcs/EN/Y2015/V9/I5/703
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