光学精密工程2017，Vol.25Issue(6)：1619-1626,8.DOI:10.3788/OPE.20172506.1619
稀疏表示下的噪声图像超分辨率重构
Reconstruction of super resolution for noise image under the sparse representation
摘要
Abstract
In order to complete the super-resolution reconstruction of noise images,a reconstruction method of noise images was introduced based on sparse representation,which could complete image de-noising and super resolution reconstruction simultaneously.Firstly,block size division was made for sample images and low-resolution images and the sample database was established.Secondly,the image degradation model was built and the way of weighted average was used for similar samples to represent the output image block with high resolution.Then,according to the input low-resolution image block,the similarity between sample block and output high-resolution image block was calculated.In addition,a similarity description method which could better reduce the influence bought by noises was proposed.Using the similarity to punish the sparse coding optimization models,a weight solving model was established.And the similar sample model could be self-adaptively searched by the model rather than being set the number of similar blocks in advance.Finally,the image block with high resolution as well as high-resolution images were reconstructed,according to the solved weight and input sample block.The result of experiment shows:compared with the other common super resolution algorithms,the peak signal to noise ratio of the mentioned method improves approximately 0.5 dB;and the reconstructed image with more details has better de-noise effect and is more suitable to practical use.关键词
超分辨率/噪声图像/稀疏表示/权值模型Key words
super resolution/noise image/sparse representation/weight model分类
信息技术与安全科学引用本文复制引用
韩玉兰,赵永平,王启松,陈欣欣,王晓飞..稀疏表示下的噪声图像超分辨率重构[J].光学精密工程,2017,25(6):1619-1626,8.基金项目
国家重点研发计划资助项目(No.2016YFB0502502) （No.2016YFB0502502）
国家自然科学基金资助项目(No.61301012) （No.61301012）
