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肖宿,韩国强,沃焱,等. 贝叶斯框架下的模糊图像盲去卷积算法[J]. 科学技术与工程, 2010, (14): .
XIAO Su,HAN Guo-qiang,WO Yan,et al.Bayesian Framework Based Blind Deconvolution Algorithm for Blurred Images[J].Science Technology and Engineering,2010,(14):.
贝叶斯框架下的模糊图像盲去卷积算法
Bayesian Framework Based Blind Deconvolution Algorithm for Blurred Images
投稿时间:2010-03-14  修订日期:2010-03-14
DOI:
中文关键词:  图像盲去卷积  贝叶斯框架  先验模型  总变分模型  数值计算
英文关键词:image blind deconvolution  Bayesian framework  prior models  total variation model  numerical calculation
基金项目:国家自然科学基金项目;国家科技支撑计划项目
           
作者单位
肖宿 华南理工大学
韩国强 华南理工大学
沃焱 华南理工大学
姚浩伟 深圳市华仁达电子有限公司
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中文摘要:
      为了去除图像模糊的同时,保持图像边缘等细节信息,需要对原始图像和点扩散函数进行准确的估计。本文在贝叶斯框架下,基于总变分模型,建立原始图像和点扩散函数的先验模型,同步估计原始图像和点扩散函数。对于总变分模型不可微分的问题,在不影响速度的前提下,用迭代重加权范数算法处理该问题。基于共轭先验理论,提出以伽马分布作为未知参数的先验模型,准确估计参数。实验证明该算法在对原始图像、点扩散函数和参数准确估计的基础上,成功地解决了模糊图像的盲去卷积问题,算法的速度和效果都得到了改进。与同类算法相比,本文提出的算法具有一定优势。
英文摘要:
      For the purpose of deblurring the blurred images without the loss of the detailed information as edges, it was necessary to estimate the original image and point spread functions accurately. This paper proposed a Bayesian framework based algorithm which used the total variation model to describe the original image. The total variation could preserve the edges of deblurred images, while it was non-differentiable. Therefore, we utilized the iteratively reweighted norm method to solve this problem. Based on the concept of the prior distribution, the Gamma distribution was introduced as the prior models of the unknown model parameters. The experimental results show the competitive performance of the proposed algorithm. With the accurate estimation of the original image and unknown model parameters, the blind devconvolution can be implemented successfully. The speed of the proposed algorithm and the results of the deconvolution are all improved obviously. Compared with the similar algorithm, the proposed algorithm has some advantages.
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