摘要
提出一种图像超分辨率复原算法,该算法考虑了运动矢量和点扩散函数估计不精确的情况。由于估计的不精确造成每帧低分辨率图像具有不同的噪声,算法根据各帧低分辨率图像的可靠性,相应地给它们赋予不同的权值,应用梯度下降法不断对权值及高分辨率图像进行更新。实验结果表明该算法较传统的MAP算法具有更好的复原效果。
Proposes an image super-resolution algorithm that takes into account inaccurate estimates of the registration parameters and the point spread function.There inaccurate estimates result in different noise level for each Low-Resolution (LR) frames.In the proposed algorithm,the LR frames are adaptively weighted according to their reliability.Using gradient descent optimization procedure,the weights are iteratively updated along with the high-resolution image.Experiment results indicate that this method is better than the conventional MAP methods on objective statistical analysis.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第34期35-37,40,共4页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60672135)。
关键词
超分辨率
图像复原
运动参数
super-resolution
image restoration : registration parameters