一种高效的图像去噪算法  

An Efficient Image Denoising Algorithm

作　　者：肖宿[1] 韩国强[1] 沃焱[1] 姚浩伟 

机构地区：[1]华南理工大学计算机科学与工程学院,广州510006 [2]深圳市华仁达电子有限公司,广东深圳518040

出　　处：《光电工程》2010年第5期116-122,共7页Opto-Electronic Engineering

基　　金：国家自然科学基金(60573019);广东省科技计划项目(2008B080701052;2009B030803004);广东省自然科学基金博士科研启动基金资助项目(7300561)

摘　　要：针对图像去噪的速度以及可能出现的阶梯效应等问题进行了研究,提出了一种高效的图像去噪算法。该算法在贝叶斯框架下,首先引入调和模型作为原始图像的先验模型,并用伽马分布作为未知参数的先验分布模型;然后,用变分近似的方法推导最大后验概率;基于此推导过程,同步地估计原始图像和未知参数的最优值,实现图像去噪。实验结果证明了该算法的高效性,通过与其它算法的比较,该算法体现了速度快、效果好的优点,且去噪后的图像不会出现阶梯效应等问题。An efficient algorithm was presented to solve the problems of the speed and the staircase effect in the image denoising. In the Bayesian framework, firstly, the harmonic model was introduced as the prior model of the original image, and the Gamma distribution was supposed to be the prior distribution model of the unknown parameters. Secondly, the maximum posteriori probability was deduced using the variational method, based on which the original image and the unknown parameters were estimated simultaneously to remove the noise in the observed image. The experimental results show the efficiency of the proposed algorithm. Furthermore, compared with other similar algorithms, the proposed algorithm shows the competitive performance on the speed without bringing the staircase effect to the denoised images.

关 键 词：图像去噪 贝叶斯框架 先验模型 调和模型 参数估计 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]