CAJ | 학술논문

针对传统图像修复方法依赖图像的结构特征和基于稀疏表示的图像修复方法未考虑修复过程中的观测噪声的问题，提出了一种基于贝叶斯压缩感知与形态学成分分析的图像修复方法。首先通过形态学成分分析法利用 Curvelet 和局部离散余弦变换分别稀疏图像的结构和纹理部分，然后用贝叶斯压缩感知得到稀疏系数的分布函数，分别求得分布函数的均值和方差，将两个均值作为结构和纹理稀疏系数的估计，方差作为噪声的估计，最后合并两部分的修复结果获得修复后的图像。仿真结果验证该方法可以提高图像的修复质量。
침대전통도상수복방법의뢰도상적결구특정화기우희소표시적도상수복방법미고필수복과정중적관측조성적문제，제출료일충기우패협사압축감지여형태학성분분석적도상수복방법。수선통과형태학성분분석법이용 Curvelet 화국부리산여현변환분별희소도상적결구화문리부분，연후용패협사압축감지득도희소계수적분포함수，분별구득분포함수적균치화방차，장량개균치작위결구화문리희소계수적고계，방차작위조성적고계，최후합병량부분적수복결과획득수복후적도상。방진결과험증해방법가이제고도상적수복질량。
To the question that traditional image inpainting methods depended on the structure characteristics of the image and the image inpainting method based on sparse representation without considering observation noise,this paper introduced an im-age inpainting method based on Bayesian compressive sensing and morphological component analysis.This algorithm trans-formed the sparsity for structure and texture with Curvelet and local discrete cosine respectively through morphological compo-nent analysis firstly.Then it got the posterior distribution function of the two sparse coefficient through Bayesian compressive sensing.It obtained the mean and the variance of the distribution function.The two means could be used as the estimation of the sparse coefficient for structure and texture of the image,and the variance was the estimation of the noise.Lastly,it obtained the inpainting image after merging the two parts.The emulation results prove that this method can improve the quality of image.