圖像模糊外文翻譯---模糊圖像的盲反卷積復(fù)原算法-文庫(kù)吧
2025-04-17 14:41 本頁(yè)面
【正文】 dge Detection. Section 4 describes the deblurring 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, parison and future work. 2 Degradation Model In 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 degraded image can be described by the following equation (1) *g H f n?? （ equation 1） In equation (1), g is degraded/blurred image, H is space invariant function (.) blurring function[3], f is an original image, and n is additive noise. The following represents the structure of degradation model. 3 Degradation Model Image deblurring can be done by the technique, Gaussian Blur. It is the convolution of the image with 2D Gaussian function. A) Gaussian Filter: Gaussian filter is used to blur an image using Gaussian function. It requires two parameters such as mean and variance. It is weighted blurring. Gaussian function is of the following form 2 2 22 / 2( , ) 1 / 2 * xyG x y e ??? ??? (equation 2) where ? is variance and x and y are the distance from the origin in the horizontal axis and vertical axis Gaussian Filter has an efficient implementation of that allows it to create a very blurry blur image in a relatively short time. B) Gaussian Noise: The ability to simulate the behavior and effects of noise is central to image restoration. Gaussian noise is a white noise with constant mean and variance. The default values of mean and variance are 0 and respectively. C) Blurring Parameter: The parameters needed for blurring an image are PSF, Blur length, Blur angle and type of noise. Point Spread Function is a blurring function. When the intensity of the observed point image is spread over several pixels, this is known as PSF. Blur length is the number of pixels by which the image is degraded. It is number of pixel position is shifted from original position. 4 Blur angle is an angle at which the image is degraded. Available types of noise are Gaussian noise, Salt and pepper noise, Poisson noise, Speckle noise which are used for blurring. In this paper, we are using Gaussian noise which is also known as White noise. It requires mean and variance as parameters. D) Algorithm for Degradation Model Input: Load an input image ‘ f’ Initialize blur length ‘ l’ Initialize blur angle ‘ theta’ Assign the type of noise ‘ n’ PSF (Point Spread Function), ‘ h’ Procedure – I h=create (f, l, theta) %Creation of PSF Blurred image (g) = f*h + n g= filter (f, h, n,” convolution” ) If ‘ g’ contains “ ringing” at its edge then Remove ringing effect using edge taper function Else Go to Procedure – II End Procedure – I 3 Canny Edge Ddtection And Ringing Effect The Discrete Fourier Transform used by the deblurring function creates high frequency dropoff at the edges of images. This high frequency dropoff can create an effect called boundary related ringing in deblurred images. For avoiding this ringing effect at the edge of image, we have to detect the edge of an image. There are various edge detection methods available to detect an edge of the image[4]. The edge can be detected effectively
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