【正文】 新疆農(nóng)業(yè)大學 英文文獻翻譯 題 目 : Restoration of Blurred Images Using Blind Deconvolution Algortithm 姓 名 : 張凡 學 院 : 計算機與信息工程學院 專 業(yè) : 信息管理與信 息系統(tǒng) 班 級 : 082 學 號 : 084631201 指 導教師 : 羅江巖 職稱 : 講師 2021 年 5 月 15 日 新疆農(nóng)業(yè)大學教務(wù)處制 1 Restoration of Blurred Images Using Blind Deconvolution Algorithm Kalasalingam University, Anand Nagar, Krishnankoil Christial Kalasalingam University, Anand Nagar, Krishnankoil Abstract: Image restoration is the process of recovering the original image from the degraded image. Aspire of the project is to restore the blurred/degraded images using Blind Deconvolution algorithm. The fundamental task of Image deblurring is to deconvolute the degraded image with the PSF that exactly describe the distortion. Firstly, the original image is degraded using the Degradation Model. It can be done by Gaussian filter which is a lowpass filter used to blur an image. In the edges of the blurred image, the ringing effect can be detected using Canny Edge Detection method and then it can be removed before restoration process. Blind Deconvolution algorithm is applied to the blurred image. It is possible to renovate the original image without having specific knowledge of degradation filter, additive noise and PSF. To get the effective results[1], the Penalized Maximum Likelihood (PML) Estimation Technique is used with our proposed Blind Deconvolution Algorithm. Key words： Blind Deconvolution Algorithm。 Canny Edge Detection。 Degradation Model。 Image restoration。 PML。 PSF 1 Introduction Image deblurring is an inverse problem which whose aspire is to recover an image which has suffered from linear degradation. The blurring degradation can be spaceinvariant or spacein variant. Image deblurring methods can be divided into two classes: nonblind, in which the blurring operator is known. And blind, in which the blurring operator is unknown[2]. Blurring is a form of bandwidth reduction of the image due to imperfect image formation process. It can be caused by relative motion between camera and original , an image can be degraded using lowpass filters and its noise. This 2 lowpass filter is used to blur/smooth the image using certain functions. Image restoration is to improve the quality of the degraded image. It is used to recover an image from distortions to its original image. It is an objective process which removes the effects of sensing environment. It is the process of recovering the original scene image from a degraded or observed image using knowledge about its nature. There are two broad categories of image restoration concept such as Image Deconvolution and Blind Image Deconvolution . Image Deconvolution is a linear image restoration problem where the parameters of the true image are estimated using the observed or degraded image and a known PSF (Point Spread Function). Blind Image Deconvolution is a more difficult image restoration where image recovery is performed with little or no prior knowledge of the degrading PSF. The advantages of Deconvolution are higher resolution and better quality. This paper is structured as follows: Section 2 describes the degradation model fo