%A Xuexia ZHONG,Guorui FENG,Jian WANG,Wenfei WANG,Wen SI %T A novel adaptive image zooming scheme via weighted least-squares estimation %0 Journal Article %D 2015 %J Front. Comput. Sci. %J Frontiers of Computer Science %@ 2095-2228 %R 10.1007/s11704-015-4179-x %P 703-712 %V 9 %N 5 %U {https://journal.hep.com.cn/fcs/EN/10.1007/s11704-015-4179-x %8 2015-09-24 %X

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.