added reports and laplacian

Author: yolanda93

Documents/Documentation.pdf

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+
+function [ decomposition_layers ] = gaussianPyramid( input_img, N )
+%gaussianPyramid Build the gaussianPyramid
+decomposition_layers=cell(1,N);
+decomposition_layers{1}=input_img; % first layer is the original image
+
+for k = 1:N-1
+gauss_img = imgaussfilt3(decomposition_layers{k}, 3); 
+aux = downsample(gauss_img,2);
+decomposition_layers{k+1}= downsample(aux',2)';
+end
+
+end
+
+
+function [ output_img ] = gaussianFilter( input_img, sigma )
+%gaussianFilter Build a 2D Gaussian Filter
+if nargin==1, sigma=0.5; end 
+x = -5:5; % sigma = 1, support = ?2:2 (N=5)
+h = exp(-(x.^2)/(2*sigma.^2)); % Gauss expression 1D
+h = h/sum(h); % Normalize; sum=1
+G = h' * h; % 2D mask
+
+output_img = imfilter(input_img,G,'same'); % convolve image 
+
+end

Documents/Report 1.pdf

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+function [ original_img ] = laplacianReconstruction( laplacian_layers, layers )
+%laplacianReconstruction 
+layers
+img_upsampled =laplacian_layers{layers}
+for k = layers-1:-1:1
+k
+original_img = uint8(laplacian_layers{k}) + uint8(img_upsampled);
+img_upsampled = upsampling(original_img);
+img_upsampled = upsampling(img_upsampled')';
+end
+%original_img = original_img
+end
+
+function [ output_img ] = upsampling( input_img )
+%gaussianPyramid Build the gaussianPyramid
+
+output_img =  zeros(size(input_img,1)*2,size(input_img,2));
+
+j=1;
+for k = 1:1:size(input_img,1)
+output_img(j,:) = input_img(k,:);
+output_img(j+1,:) = input_img(k,:);
+j=j+2;
+end
+
+end

Documents/Report 2.pdf

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+img1 = imread('cameraman.tif');
+img2 = imread('lena_gray_512.tif');
+img3 = imread('mandril_gray.tif');
+
+
+figure(1);
+layers=5;
+gaussian_layers= gaussianPyramid(img2,layers);
+
+for k = 1:layers
+subplot(1,layers,k),imshow(gaussian_layers{k});
+end
+
+
+layers=5;
+laplacian_layers= pyramidLaplacian(img2,layers);
+
+figure(2);
+for k = 1:layers
+subplot(1,layers,k),imshow(laplacian_layers{k});
+end
+
+figure(3);
+%synthesis
+original_img = laplacianReconstruction(laplacian_layers, layers);
+
+imshow(original_img);

Documents/TD3-entropy.txt

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+function [ laplacian_layers ] = pyramidLaplacian( input_img, N )
+%pyramideLaplacian laplacian pyramid
+% N decomposition layers
+
+laplacian_layers=cell(1,N);
+% Convolve the filtered image with the gaussian filter
+decomposition_layers = gaussianPyramid( input_img, N );
+
+for k = 1:N-1
+ 
+img_upsampled = upsampling(decomposition_layers{k+1});
+img_upsampled = upsampling(img_upsampled')';
+
+% Construct N Laplacian descomposition layer
+laplacian_layers{k}= uint8(decomposition_layers{k}) - uint8(img_upsampled);
+end
+laplacian_layers{N} = imgaussfilt3(decomposition_layers{N-1}, 3);
+
+end
+
+function [ output_img ] = upsampling( input_img )
+%gaussianPyramid Build the gaussianPyramid
+
+output_img =  zeros(size(input_img,1)*2,size(input_img,2));
+
+j=1;
+for k = 1:1:size(input_img,1)
+output_img(j,:) = input_img(k,:);
+output_img(j+1,:) = input_img(k,:);
+j=j+2;
+end
+
+end
+
+function [ output_img ] = gaussianFilter( input_img, sigma )
+%gaussianFilter Build a 2D Gaussian Filter
+if nargin==1, sigma=0.5; end 
+x = -5:5; % sigma = 1, support = ?2:2 (N=5)
+h = exp(-(x.^2)/(2*sigma.^2)); % Gauss expression 1D
+h = h/sum(h); % Normalize; sum=1
+G = h' * h; % 2D mask
+
+output_img = imfilter(input_img,G,'same'); % convolve image 
+
+end
+