MATLAB Image Tool Box Image Restoration Using MATLAB

MATLAB Image Tool Box : Image Restoration Using MATLAB Image Tool. Box Visual Communication Lab Han Jae Hyeck 98. 10. 29 1 영상통신연구실 한재혁

MATLAB Image Tool Box : Image Restoration - Image Degradation sensor noise, blur due to camera misfocus, relative object-camera motion, random atmospheric turbulence, etc. - Image Restoration filtering the image to minimize the effect of degradation Imaging system A to D conversion Digital filter D to A conversion Display or record Digital Image restoration system - MATLAB Image Toolbox Noise Removal. linear filtering - filter 2 median filtering - medfilt 2 adaptive filtering - wiener 2 2 영상통신연구실 한재혁

MATLAB Image Tool Box : Image Restoration - Wiener Filter Observed image f defined as below f=s+b s = signal, b = additive noise if the wiener filter presented with the sum f=s+b the signal and the noise as input, the output is optimality criterion for choosing h is a minimum signal distance in the mean of correlation the wiener filter 4 영상통신연구실 한재혁

MATLAB Image Tool Box : Image Restoration - WIENER 2 Algorithm - 지역의 평균과 표준편차 여기서 은 image의 각 pixel의 M by N 이웃 구역 - pixel-wise Wiener filter 2 여기서 V 는 noise 의 variance J = WIENER 2( I, [ M N ], NOISE ) 이미지 I를 pixel-wise adaptive Wiener filtering. 이웃 픽셀은 M-by-N 으로 결정되고 평균과 표준 편차를 결정. [M N]의 기본값은 3. 첨가된 noise는 mean power가 NOISE 인 white Gaussian noise 로 가정. [ J , NOISE ] = WIENER 2( I, [ M N ]) filtering 전에 noise power를 측정하여 가정. 5 영상통신연구실 한재혁

MATLAB Image Tool Box : Image Restoration Example ) I = imread('saturn. tif'); J = imnoise(I, 'gaussian', 0, 0. 005); K = wiener 2(J, [5 5]); imshow(J), figure, imshow(K) 6 영상통신연구실 한재혁