is their a problem with the blurring filter in the given code?? the image as a result is divided into 4 blocks which are out of order....... how can i blur it properly?

Question

shawn 2012-7-18

0
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https://ww2.mathworks.cn/matlabcentral/answers/43933-is-their-a-problem-with-the-blurring-filter-in-the-given-code-the-image-as-a-result-is-divided-int

i m trying to blur an image and then deblur it using a wiener filter that i created. but the blurred image shows unexpected results. it appears the image is getting divided into blocks which are then arranged out o order. what's the issue.?

i am trying to create a wiener filer to blur the image. i use a low pass LSI filter and then add gaussian noise to the blurred image. i assume the expected noise to be white and hence has a flat spectral density.

but before i can create by wiener filter to deblur it, the blurring filter(h) gives unexpected results. i am highlighting in bold letters the portion i assume is creating the problem. will the code not workfor those images for which number of rows is not eual to number of columns? in any case, its not working i guess when rows = columns either......please help me in correcting the error. in my code:

h=low pass filter
Snn=noise power
Suu = signal power

Code:

% function wien2(name,xdim,No,Snn)
%
% name = 'input image' (as in 'lenna.256')
% xdim = x dimension of input image (usually 256 or 512)
% No   = Variance of Noise
% Snn  = Power Spectral Density of Noise (Assumed White)
%
% This function takes an input image, runs it through a LSI filter h,
% and adds Gaussian noise to it.  The MSE between the degraded and
% original image is then calculated.  Weiner Filtering is then performed
% (using known h) and the degraded image is restored using
% the filter.  The MSE between the restored and original image is then
% calculated and returned.  Snn is set to a constant (assumes white noise)
%
No = 80;
% Load and Plot image
pict = imread('C:\Documents and Settings\All Users\Documents\My Pictures\Matlab pics\planet.png');
pict=rgb2gray(pict)
;
[xdim xdim]=size(pict)
;
clf
subplot(221)
imagesc(pict);
colormap(gray);
txt = ' before degradation';
title(txt)
axis square
axis off

*% Create LSI degradation model, need it to be phaseless

hi = 3.5^(-2);
h = zeros(256);
xl = 4;
xh = xdim - xl + 2;
h(1:xl,1:xl) = hi;
h(xh:xdim,1:xl) = hi;
h(1:xl,xh:xdim) = hi;
h(xh:xdim,xh:xdim) = hi;
% Create Gaussian noise, mean = 0, variance comes from input (No)
noise = sqrt(No)*randn(xdim,xdim);
% Run image through LSI Filter and then add noise
dpict = imfilter(pict,h);
dpict =double(dpict)+noise;
% Plot degraded image
subplot(222)
imagesc(dpict);
colormap(gray);
txt = [' with additive Gaussian Noise (mean=0, var=' , num2str(No), ')'];
title(txt)
axis square
axis off