Working version Quatizer and Haar transform

Author: iuya

Documents/TD2016.pdf

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+% dequantize_matrix:
+% Uniformly proyects a matrix with a number of levels (2^old_bytesize)
+% into a new matrix with a number of levels (2^new_bytesize)
+%  
+% Correct behaviour only when: 
+%   new_bytesize >= old_bytesize
+function dequantized_matrix = dequantize_matrix(matrix, old_bytesize, new_bytesize)
+    delta = 2^(new_bytesize-old_bytesize);
+    dequantized_matrix = zeros(size(matrix,1),size(matrix,2),'uint8');
+    for row = 1:size(matrix,1)
+        for col = 1:size(matrix,2)
+            dequantized_matrix(row,col) = dequantize(matrix(row,col), delta);
+        end
+    end
+end
+
+function dequantization = dequantize(pixel, delta)
+    % Operation avg*Pixel+avg changed to:
+    dequantization = delta*(double(pixel) + 0.5);
+end

Quantization/dequantization.m

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+function quantized_matrix = quantize_matrix(matrix, new_bytesize)
+    quantized_matrix = zeros(size(matrix,1),size(matrix,2),'uint8');
+    for row = 1:size(matrix,1)
+        for col = 1:size(matrix,2)
+            quantized_matrix(row,col) = quantize(matrix(row,col), new_bytesize);
+        end
+    end
+end
+
+function quantization = quantize(pixel, new_bytesize)
+    dif_levels = 2^(8-new_bytesize);
+    quantization=floor(double(pixel)/dif_levels);
+end

Quantization/dequantize_matrix.m

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+% haar_reverse:
+% Given an input haar_transform image of 256 levels, undo the transform.
+function haar_matrix = haar_reverse(original_matrix)
+    temp_matrix = transpose(original_matrix);
+    temp_matrix = revert_haar(temp_matrix);
+    temp_matrix = transpose(temp_matrix);
+    haar_matrix = revert_haar(temp_matrix);
+end
+
+function haar_matrix = revert_haar(matrix)
+    haar_matrix = zeros(size(matrix,1),size(matrix,2));
+    half_col = size(matrix,2)/2;
+    for row = 1:size(matrix,1)
+        i = 1;
+        for col = 1:half_col
+            haar_matrix(row,i) = matrix(row,col) + matrix(row,col + half_col);
+            haar_matrix(row,i+1) = matrix(row,col) - matrix(row,col + half_col);
+            i = i + 2;
+        end
+    end
+end

Quantization/quantization.m

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+function haar_matrix = haar_reverse_multilevel(original_matrix, n_transforms)
+    haar_matrix = original_matrix;
+    for i = n_transforms-1:-1:0
+        rows = 1:(size(haar_matrix,1)/2^i);
+        columns = 1:(size(haar_matrix,1)/2^i);
+        haar_matrix(rows,columns) = haar_reverse(haar_matrix(rows,columns));
+    end
+end

Quantization/quantization2.m

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+function haar_matrix = haar_reverse_multilevel2(original_matrix, n_transforms)
+    haar_matrix = original_matrix;
+    for i = n_transforms:1
+        rows = 1:(size(haar_matrix,1)/2^i);
+        columns = 1:(size(haar_matrix,1)/i);
+        haar_matrix(rows,columns) = haar_reverse(haar_matrix(rows,columns));
+    end
+end

Quantization/quantize_matrix.m

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+% haar_transform:
+% Given an input greyscale image of 256 levels, apply the harr transform
+% to it.
+% Will apply the transform first to the rows and then to the columns
+% Parameteres:
+%   matrix: the image to be transformed
+function haar_matrix = haar_transform(original_matrix)
+    temp_matrix = haar_pass(original_matrix);
+    temp_matrix = transpose(temp_matrix);
+    temp_matrix = haar_pass(temp_matrix);
+    haar_matrix = transpose(temp_matrix);
+end
+
+function haar_matrix = haar_pass(matrix)
+    haar_matrix = zeros(size(matrix,1),size(matrix,2));
+    half_col = size(matrix,2)/2;
+    for row = 1:size(matrix,1)
+        i = 1;
+        for col = 1:2:size(matrix,2)
+            haar_matrix(row,i) = (double(matrix(row,col))+ double(matrix(row,col+1)))/2;
+            c = (double(matrix(row,col)) - double(matrix(row,col+1)))/2;
+            haar_matrix(row,i+half_col) = c ;
+            i = i + 1;
+        end
+    end
+end

Test-images/cameraman.tif

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+function haar_matrix = haar_transform_multilevel(original_matrix, n_transforms)
+    haar_matrix = original_matrix;
+    for i = 1:n_transforms
+        rows = 1:size(haar_matrix,1)/i;
+        columns = 1:size(haar_matrix,1)/i;
+        haar_matrix(rows,columns) = haar_transform(haar_matrix(rows,columns));
+    end
+end