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?

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

[Sebastian Holmqvist]

This is exhausting to read. Please reformulate your question and format your code with the Code button.