改进的稀疏表示超分辨率图像重建  

Improved Sparse Representation of Super-Resolution Image Reconstruction

作　　者：廖成 郭心悦[1] 韩彦芳[1] LIAO Cheng;GUO Xin-yue;HAN Yan-fang(School of Optical-Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学光电信息与计算机工程学院,上海200093

出　　处：《软件导刊》2019年第2期137-140,共4页Software Guide

摘　　要：为了能从单幅低分辨率图像中利用超分辨率技术重建出高分辨率图像,提出一种基于稀疏表示的改进算法。首先求出在低分辨率图像过完备字典上的稀疏表示系数,将稀疏表示系数与高分辨率图像的过完备字典相结合,得到高分辨率图像块,再联合输入的低分辨率图像块与生成的高分辨率图像块,求解出其在高低分辨率字典对上的稀疏系数,最后结合高分辨率图像字典,得到更加精确的高分辨率图像块。经仿真实验验证,该改进方法有效提升了重建图像质量,增强了重建图像的还原度。In order to reconstruct high-resolution images from single low-resolution images,we proposed an improved algorithm based on sparse representation.we solved the low resolution images'sparse representation coefficients on the complete dictionary and combined with high resolution images of the complete dictionary to get high resolution image patches by the sparse linear combination of the dictionary through jointing input low-resolution image and generated new high-image patches,and then used the sparse coefficients combined with the dictionary and outputed more accurate high-resolution image patches.The results of simulation experiments show that the improved algorithm is effective to improve the quality of the reconstruction of high-resolution image.

关 键 词：稀疏表示 超分辨率 图像重建 高低分辨率图像块 稀疏系数 

分 类 号：TP317.4[自动化与计算机技术—计算机软件与理论]