圖像處理外文翻譯---模糊圖像的盲反卷積復(fù)原算法

1、新疆農(nóng)業(yè)大學(xué) 新疆農(nóng)業(yè)大學(xué)英文文獻(xiàn)翻譯 英文文獻(xiàn)翻譯題 目: Restoration of Blurred Images Using BlindDeconvolution 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2low-pass filter is used

2、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

3、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

4、 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

5、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 Deconvoluti

6、on are higher resolution and better quality.This paper is structured as follows: Section 2 describes the degradation model for blurring an image. Section 3 represents Canny Edge Detection. Section 4 describes the deblurr

7、ing algorithm and overall architecture of this paper. Section 5 describes the sample results for deblurred images using our proposed algorithm. Section 6 describes the conclusion, comparison and future work.2 Degradation

8、 ModelIn degradation model, the image is blurred using filters and additive noise. Image can be degraded using Gaussian Filter and Gaussian Noise. Gaussian Filter represents the PSF which is a blurring function. The degr

9、aded image can be described by the following equation (1)（equation * g H f n ? ?1）In equation (1), g is degraded/blurred image, H is space invariant function (i.e.) blurring function[3], f is an original image, and n is