R. Fabian and D. Malah. Robust identification of motion and out-of-focus blur parameters from blurred and noisy images. CVGIP: Graphical Models and Image Processing, 53(5):403--412, September 1991.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....estimation of the motion blur parameters has used di#erent methods as the bispectrum [7] or the Discrete Cosine Transform [23] in both cases the orientation of the motion was assumed known, assumption that was false in a lot of the applications. Ideal motion blur can be described mathematically [8] as the result of a linear filter b(x, y) i(x, y)#h(x, y)wherei is the theoretical image taken with an exposure time T e =0,b is the real blurred image, and h the point spread function (PSF) Given an angle= # and the length d = V o T e ,whichis the number of scene points that a#ect a specific ....

R. Fabian and D. Malah. Robust identification of motion and out-of-focus blur parameters from blurred and noisy images. CVGIP: Graphical Models and Image Processing, 53(5):403--412, September 1991.

.... is characterized by almost periodic circles with zero valued H(u; v) This occurs for r satisfying: 2Rr = 3:83; 7:02; 10:2; 13:3; 16:5 : The well defined structure of H(u; v) zeros in the case of motion and misfocus blur is used for the identification of the blur parameter (Cannon, 1976; Fabian and Malah, 1991) for purpose of image restoration. 3.1.3 Gaussian blur Gaussian blur, which is often used, can be caused by atmospheric and optical blur. It is known that the lens of the eyes blur images in this manner. Computer tomography images also suffers from Gaussian blur (Kimia and Zucker, 1993) The ....

Fabian, R. and Malah, D. (1991). Robust identification of motion and out-of-focus blur parameters from blurred and noisy images. cvgip, 53(5):403--412.

....value. Assuming that the power spectrum of the image has no zeros, an estimate of the PSF s parameter value is made using the location of the zeros of the power spectrum of the degraded image [13] A major drawback of these methods is their high sensitivity to noise. More robust techniques [14] [15]have been proposed to improve the accuracy of the identification of the spectral nulls in the presence of noise# however, such methods cannot identify PSFs that do not possess any spectral nulls, such as the Gaussian PSF. Other techniques are based on local image characteristics. A point source, ....

R. Fabian and D. Malah, "Robust identification of motion and out-of-focus blur parameters from blurred and noisy images," CVGIP: Graphical Models and Image Processing,vol. 53(5), pp. 403-412, Sept. 1991.

....estimation of the motion blur parameters has used different methods as the bispectrum [7] or the Discrete Cosine Transform [23] in both cases the orientation of the motion was assumed known, assumption that was false in a lot of the applications. Ideal motion blur can be described mathematically [8] as the result of a linear filter b(x; y) i(x; y) h(x; y) where i is the theoretical image taken with an exposure time T e = 0, b is the real blurred image, and h the point spread function (PSF) Given an angle= ff and the length d = V o Theta T e , which is the number of scene points that ....

R. Fabian and D. Malah. Robust identification of motion and out-of-focus blur parameters from blurred and noisy images. CVGIP: Graphical Models and Image Processing, 53(5):403--412, September 1991.

.... a uniform background found in applications such as astronomical speckle imaging [3] edges common in non destructive industrial x ray imaging [22] and frequency domain nulls found in situations in which the blurring results from camera misfocus and linear motion [23] 24] among others [25] [26]. Once the PSF has been completely identified, one of the classical restoration techniques is used to estimate the true image. A priori blur identification techniques are the simplest class of blind deconvolution methods to implement and have low computational requirements. They are applicable to ....

R. Fabian and D. Malah, "Robust identification of motion and out-of-focus blur parameters from blurred and noisy images," CVGIP: Graphical Models and Image Processing, vol. 53(5), pp. 403-412, Sept. 1991.

....known, and therefore there is no need for estimating them. Usually, in addition to the motion blur, there are also other kinds of noise present in the image, so a more CHAPTER 2. BACKGROUND: OPTICAL FLOW AND MOTION BLUR 17 robust estimation of the motion blur parameters is needed. One approach, [8] which is working for both motion and out of focus blur, is to proceed in two stages. First, the degraded image is processed in order to improve the SNR and then the algorithm that extracts the blur parameters is applied. This approach assumes a model for the degraded image as given in equation ....

....equation 2.9 where g(i; j) is the degraded image, f(i; j) is the ideal image, h(i; j) the PSF, and n(i; j) additional noise. g(i; j) f(i; j) h(i; j) n(i; j) 2:9) The h(i; j) for the case of motion blur created by uniform motion across the X axis is given in equation 2.10. The algorithm in [8] is developed only for this specific case and therefore it is clear that equation 2.10 is just a sub case of equation 2.8 that we analyse at the definition of motion blur. h(i; j) 8 : 1 d ; Gammad=2 i d=2; j = 0 0; otherwise fi fi fi fi fi fi fi (2:10) At this point we have to ....

[Article contains additional citation context not shown here]

R. Fabian and D. Malah. Robust identification of motion and out-of-focus blur parameters from blurred and noisy images. CVGIP: Graphical Models and Image Processing, 53(5):403--412, September 1991.

No context found.

R. Fabian and D. Malah. Robust identification of motion and out-of-focus blur parameters from blurred and noisy images. CVGIP: Graphical Models and Image Processing, 53(5):403--412, September 1991.

No context found.

R. Fabian and D. Malah, "Robust identification of motion and out-of-focus blur parameters from blurred and noisy images," CVGIP: Graphical Models and Image Processing, vol. 53, pp. 403-412, Sept. 1991.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC