基于稀疏表示的红外视频图像超分辨率算法  

Super-resolution Algorithm of Infrared Video Image Based on Sparse Representation

作　　者：戚曹 朱桂斌[1] 唐鉴波[1] 牟宇飞[1] 

机构地区：[1]重庆通信学院应急通信重庆市重点实验室,重庆400035

出　　处：《计算机工程》2016年第3期278-282,共5页Computer Engineering

基　　金：国家自然科学基金资助项目(61272043);应急通信重庆市重点实验室开放课题基金资助项目(CQKLEC;20120504);重庆通信学院理论研究基金资助项目(TZ-CQTY-Y-C-2014-022)

摘　　要：针对红外视频图像低分辨率的特点,提出一种改进的红外视频图像超分辨重建算法。研究低分辨率红外视频图像块的稀疏表示,通过最小角度回归算法求解得到稀疏表示的最优化系数,并利用该系数产生重建约束后的高分辨率视频图像最终解,实现对红外视频图像的超分辨率重建。实验结果表明,对于红外视频序列图像,该算法在主观视觉效果和客观评价方面均优于Bicubic,NE和UVII算法。According to the lowresolution characteristic of infrared video image,an improved super-resolution reconstruction algorithm of infrared video image is proposed in this paper. It researches the sparse representation for the low-resolution infrared video image patches,and gets the optimum coefficients of sparse representation by Least Angle Regression（ LAR） algorithm. By reconstruction constraints,the final high-resolution video image can be obtained through the optimun coefficients. Experimental results showthat,for infrared video images,the proposed algorithm can improve the resolution of the input image significantly and achieve better outcomes in visual effects and objective evaluation,compared with Bicubic,NE and UVII algorithms.

关 键 词：稀疏表示 红外视频图像 最小角度回归算法 超分辨率 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]