圖像模糊外文翻譯---模糊圖像的盲反卷積復(fù)原算法(存儲(chǔ)版)
【正文】 題 目 : Restoration of Blurred Images Using Blind Deconvolution Algortithm 姓 名 : 學(xué) 院 : 專 業(yè) : 班 級(jí) : 學(xué) 號(hào) : 指 導(dǎo)教師 : 職稱 : 新疆農(nóng)業(yè)大學(xué)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。 then replacing the center pixels of the blurred image with the original image. 4 Overall Architecture And Deblurring Algorithm The following Fig. 2 represents the overall architecture of this paper. The original image is degraded or blurred using degradation model to produce the blurred image. The blurred image should be an input to the Deblurring algorithm. Various algorithms are available for deblurring. In this paper, we are going to use Blind Deconvolution Algorithm. The result of this algorithm produces the deblurring image which can be pared with our original image[5]. 6 Overall Architecture A) Blind Deconvolution Algorithm: Blind Deconvolution Algorithm can be used effectively when no information of distortion is known. It restores image and PSF simultaneously. This algorithm can be achieved based on Maximum Likelihood Estimation (MLE) [6]. Algorithm for Deblurring: Input: Blurred image ‘ g’ Initialize number of iterations ‘ i’ Initial PSF ‘ h’ Weight of an image ‘ w’ % pixels considered for restoration a=0 (default) %Array corresponding to additive noise Procedure – II If PSF is not known then Guess initial value of PSF Else Specify the PSF of degraded image Restored Image f’= Deconvolution (g, h, i, w, a) End Procedure – II 7 5 Sample Rrsults The below images represent the result of degradation model using Gaussian blur. First image represented the original image and its edge can be estimated by Canny Edge detection method. Original Image The edge detection can be applicable to Gray Image. Therfore the origianl RGB image can be converted to gray image. After that Canny Edge Detection is applied for getting the Edges of the original image. 8 Edges of original Image The original can
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