denoisewpyr.m

MATLAB Denoising software for grayscale images

function im_d = denoiseWpyr(im,noiseVar,noise,opts);

% function im_d = denoiseWpyr(im,noiseVar,noise,opts);
%
% Denoise image using a quadrature mirror filter Wavelet decomposition with 
% oriented highpass residual bands. Called from 'denoise_main' 
%
% where
%   'im'        is the noisy image
%   'noiseVar'  is the noise variance
%   'noise'     a noisy image to estimate the covariance
%   'opts'      a set of options, see 'newOptions'
%
% Peter-Vincent Gehler 15.March 2005


verbose = 1;

% The number of orientations is 3, regardless what the user specified. 
opts.nOrientations = 3;

% noise without boundary extension to avoid bnry effect in the covariance
% matrix
noise = sqrt(noiseVar) * randn(size(im));

% build the pyramid representation ...
[pyr,pind] = buildWpyr(im,opts.nLevels,'qmf9','circular');
[pyrN,pind] = buildWpyr(noise,opts.nLevels,'qmf9','circular');
pyrnew = pyr;

numOfBands = size(pind,1);

% For each subband ....
for nband = 1:numOfBands-1
    if verbose 
        fprintf('processing band no %d\n',nband);
    end
    % ... decide on wether include the parent or not ...
    prnt = opts.parent & (nband+opts.nOrientations <= numOfBands-1);
    
    % ... denoise ...
    newBand = denoise_band(pyr,pyrN,pind,nband,opts,prnt);
    
    % ... and store the result.
    pyrnew(pyrBandIndices(pind,nband)) = newBand(:);
end

% Reconstruct the image and return.
im_d = reconWpyr(pyrnew,pind,'qmf9','circular');