A novel adaptive image zooming scheme via weighted least-squares estimation

作     者：Xuexia ZHONG Guorui FENG Jian WANG Wenfei WANG Wen SI 

作者机构：Cyber Physical System Research and Development Center The Third Research Institute of Ministry of Public Security Shanghai 201204 China School of Communication and Information Engineering Shanghai University Shanghai 200444 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai 200240 China Shanghai Chenrui Information Technology Company Shanghai 201204 China College of Information and Computer Science Shanghai Business School Shanghai 201400 China 

出 版 物：《Frontiers of Computer Science》 (中国计算机科学前沿（英文版）)

年 卷 期：2015年第9卷第5期

页      面：703-712页

核心收录：

学科分类：08[工学] 080203[工学-机械设计及理论] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 

基　　金：Acknowledgements Our research was supported by the following projects: National Natural Science Foundation of China (Grants No. 61373151) National High-tech R&D Program of China (2013AA01A603) National Science and Technology Support Projects of China (2012BAH07B01) Program of Science and Technology Commission of Shanghai Municipality (12510701900) 2012 loT Program of Ministry of Industry and Information Technology of China 

主　　题：adaptive interpolation refinement strategy,weighted least-squares estimation arbitrary integer and WLS-AIZ scheme 

摘      要：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 x 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 through weighted 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 comparing WLS-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.