testdwt.m

denoising image with DWT

clear all
close all

clc
J=imread('cell.jpg');
figure, imshow(J)
J=RGB2GRAY(J);
S=size(J);
[Lo_D,Hi_D,Lo_R,Hi_R] = wfilters('db1');
[ca,chd,cvd,cdd] = dwt2(J,Lo_D,Hi_D);

%normalisation des coifficients dans l'intervalle [0 1]
min_ca=min(min(ca));
max_ca=max(max(ca));
caa=((ca-min_ca)./(max_ca-min_ca));
figure,imshow([caa,chd;cvd,cdd]);

%decomposition a l'閏helle2
% [ca2,chd2,cvd2,cdd2] = dwt2(ca,Lo_D,Hi_D);
% min_ca2=min(min(ca2));
% max_ca2=max(max(ca2));
% caa2=((ca2-min_ca2)./(max_ca2-min_ca2));
% figure,imshow([caa2,chd2;cvd2,cdd2]);


%[M N]size(ca);
%recontruction de l'image contour
X_cont = idwt2(zeros(size(ca)),chd,cvd,cdd,'db1',S*2 );
figure, imshow(X_cont)

% X_cont = idwt2(zeros(size(ca2)),chd,cvd,cdd,'db1',S/2 );
% figure, imshow(X_cont)

%histogramme de l'image contour
min_X_cont=min(min(X_cont));
max_X_cont=max(max(X_cont));
XX_cont=((ca-min_X_cont)./(max_ca-min_X_cont));
size(XX_cont)
figure, imhist(XX_cont)