小波多尺度分析目标图像复原

为了有效复原模糊图像以得到可辨识的目标图像，需要根据目标图像的纹理特征来进行有约束的正则化复原。针对大尺度模糊图像的复原处理，通过分析常见的自适应正则化方法在抑制噪声及虚假波纹方面存在的问题，提出基于小波多尺度分析的正则化复原方法，该方法利用小波变换的多尺度分析技术直接分析模糊图像，结合形态学操作得到合理反映目标棱边分布的图像，并利用该图像加权调节正则化参数进行复原操作。实验表明该算法能够有效处理大尺度模糊，并能够较快地收敛到易于辨识的目标图像。

Restoration of target image based on wavelet multi-resolution analysis

In order to restore blurred image to get the recognizable target,the adaptive regularized image restoration algorithm is adopted according to the detail character of target image.This paper emphasizes on discussing restoration method of the high degree blurred image.Through analyzing the limitation of some popular edge distribution estimation method which is used to restrain noise and faint edges,this paper proposes the method of image restoration based on wavelet multi-resolution analysis.Using wavelet-based multi-resolution analysis technique combined with morphology operator,the method works on the blurred image directly and obtains the edge weight image which can indicate edge distribution of original image reasonably.Last,the weight image is used as the adaptive condition to carry through image restoration.The experimental results indicate that the method can dispose the high degree blurred image effectively and help the restoration process converge quickly to gain the satisfying result.