基于聚类的单帧图像超分辨率重建方法  

Super-resolution Reconstruction Method for Single Frame Image Based on Clustering

作　　者：李娟娟[1] 李小红[1] 

机构地区：[1]合肥工业大学计算机与信息学院,合肥230009

出　　处：《计算机工程》2013年第7期284-287,共4页Computer Engineering

摘　　要：为解决单幅图像的超分辨重建问题,提出一种基于聚类的单帧图像超分辨率重建方法。从高分辨率样本图像中学习一个结构聚类型的高分辨率字典,利用迭代收缩算法优化目标方程,求得高分辨率图像的表示系数,使用学习到的高分辨率字典对低分辨率图像进行重构。实验结果表明,与总变分方法、软切割方法和稀疏表示方法相比,该方法的单帧图像超分辨率重建效果较好。To the question of single frame image super-resolution, implement single frame image super-resolution with the prior of training images, this paper proposes a single frame image super-resolution reconstruction method based on clustering. It builds a structural clustering based high-resolution dictionary from a set of high-resolution images, optimizes objective equation by using iterative shrinkage solution to solve the representation coefficient of high-resolution image, reconstructs low-resolution image by exploiting the learned high-resolution dictionary. Experimental results show that compared with Total Variation（TV） method, Softcuts method and Sparse Representation（SR） method, the effect of the single flame image super-resolution reconstruction of this method is better.

关 键 词：超分辨率 稀疏表示 重建方法 聚类 字典 迭代 

分 类 号：TN911.73[电子电信—通信与信息系统]