and
這學期的數位視訊系統老師叫我們寫一個作業，題目:
是說把一張彩色的圖以RBG為做向量(vector)，再透過generalized Lloyd algorithm去把圖片重新編碼。
大學時都沒這麼認真用過MATLAB! @@
glloyd_training.m
檔名在VQ.m是寫死的
把程試簡化，讓助教比較好處理。
跑幾張圖來試試看好了!
source
VQ(8)
VQ(32)
VQ(128)
居然V32就已經看不太出來有什麼差別了.
這個故事告訴我們，"做影像處理的報告，乖乖的用Lenna就對了"
matlab code參考自:
http://www.wretch.cc/blog/Lak4CYUT/3518815
是說把一張彩色的圖以RBG為做向量(vector)，再透過generalized Lloyd algorithm去把圖片重新編碼。
大學時都沒這麼認真用過MATLAB! @@
glloyd_training.m
function [codebook, Index] = glloyd_training(ImgPxl, CS, Vector_Len, er, x, y)
Training_idx = (x*y*3)/Vector_Len ;
Training_set = reshape(ImgPxl(:), Training_idx, Vector_Len);
codebook = zeros(CS, Vector_Len) ;
Child_group = fix(Training_idx/CS); %每個codebook 值將會代表幾個原始值,取整數
for i = 1 : CS %先分成codesize 區塊，每一塊先取平均值
codebook(i,:) = mean(Training_set(((i-1)*Child_group+1):i*Child_group,:) );
end
old_MSE = 0;
inited=0;
MSE_diff=100;
min_diff =2;
%新舊codebook 的MSE相差小於min_diff,就不再做下去. 當作是完成了.
while (MSE_diff>min_diff)
if (inited>0)
for i = 1 : CS
same_group = find(Index == i) ;
if ~isempty(same_group)
codebook(i, :) = mean(Training_set(same_group, :));
else %沒有任何值落在這邊 就抓附近的來補一下
if i == 1
codebook(i,:) = mean(codebook([2 3],:)) ;
elseif i == CS
codebook(i,:) = mean(codebook([CS-1 CS-2],:)) ;
else
codebook(i,:) = mean(codebook([i+1 i-1],:)) ;
end
end
end
else
inited =1;
end
coded_value = zeros(Training_idx,1);
%將所有的vector 依codebook分類
for i = 1 : Training_idx
Current_Vector = Training_set(i,:);
%分身為CS筆
Current_Vector_n = Current_Vector(ones(CS,1),:);
%算出MSE
vector_MSE = sum(((Current_Vector_n-codebook).^2).')/Vector_Len ;
%選MSE最小的
[coded_value(i), Index(i)] = min(vector_MSE) ;
end
VQImg = codebook(Index,:) ;
VQImg = reshape(VQImg(:), y, x, 3) ;
MSE = mse(ImgPxl - VQImg);
if (old_MSE)
MSE_diff = abs(old_MSE-MSE);
else
MSE_diff = abs(MSE);
end
old_MSE= MSE;
MSE_diff
end
Training_idx = (x*y*3)/Vector_Len ;
Training_set = reshape(ImgPxl(:), Training_idx, Vector_Len);
codebook = zeros(CS, Vector_Len) ;
Child_group = fix(Training_idx/CS); %每個codebook 值將會代表幾個原始值,取整數
for i = 1 : CS %先分成codesize 區塊，每一塊先取平均值
codebook(i,:) = mean(Training_set(((i-1)*Child_group+1):i*Child_group,:) );
end
old_MSE = 0;
inited=0;
MSE_diff=100;
min_diff =2;
%新舊codebook 的MSE相差小於min_diff,就不再做下去. 當作是完成了.
while (MSE_diff>min_diff)
if (inited>0)
for i = 1 : CS
same_group = find(Index == i) ;
if ~isempty(same_group)
codebook(i, :) = mean(Training_set(same_group, :));
else %沒有任何值落在這邊 就抓附近的來補一下
if i == 1
codebook(i,:) = mean(codebook([2 3],:)) ;
elseif i == CS
codebook(i,:) = mean(codebook([CS-1 CS-2],:)) ;
else
codebook(i,:) = mean(codebook([i+1 i-1],:)) ;
end
end
end
else
inited =1;
end
coded_value = zeros(Training_idx,1);
%將所有的vector 依codebook分類
for i = 1 : Training_idx
Current_Vector = Training_set(i,:);
%分身為CS筆
Current_Vector_n = Current_Vector(ones(CS,1),:);
%算出MSE
vector_MSE = sum(((Current_Vector_n-codebook).^2).')/Vector_Len ;
%選MSE最小的
[coded_value(i), Index(i)] = min(vector_MSE) ;
end
VQImg = codebook(Index,:) ;
VQImg = reshape(VQImg(:), y, x, 3) ;
MSE = mse(ImgPxl - VQImg);
if (old_MSE)
MSE_diff = abs(old_MSE-MSE);
else
MSE_diff = abs(MSE);
end
old_MSE= MSE;
MSE_diff
end
廣告
VQ.mfunction VQ(CS)
er = 5;
ImgFile = 'Lena.jpg';
ImgPxl = double(imread(ImgFile)) ;
Pic_info = imfinfo(ImgFile);
[codebook, index] = glloyd_training(ImgPxl, CS, Vector_Len, er, Pic_info.Width, Pic_info.Height) ;
VQImg = codebook(index,:) ;
VQImg = reshape(VQImg(:), Pic_info.Height, Pic_info.Width, 3) ;
MSE = mse(ImgPxl - VQImg)
index = gcf();
if (index ==1)
figure(index);
imshow(uint8(ImgPxl)) ;
title('Source' ) ;
end
figure(index+1) ;
imshow(uint8(VQImg)) ;
title(['VQ L=',int2str(CS)] );
%Usage: VQ(CS)
%CS is codebook size(L)
Vector_Len = 3;er = 5;
ImgFile = 'Lena.jpg';
ImgPxl = double(imread(ImgFile)) ;
Pic_info = imfinfo(ImgFile);
[codebook, index] = glloyd_training(ImgPxl, CS, Vector_Len, er, Pic_info.Width, Pic_info.Height) ;
VQImg = codebook(index,:) ;
VQImg = reshape(VQImg(:), Pic_info.Height, Pic_info.Width, 3) ;
MSE = mse(ImgPxl - VQImg)
index = gcf();
if (index ==1)
figure(index);
imshow(uint8(ImgPxl)) ;
title('Source' ) ;
end
figure(index+1) ;
imshow(uint8(VQImg)) ;
title(['VQ L=',int2str(CS)] );
檔名在VQ.m是寫死的
ImgFile = 'Lena.jpg';
把程試簡化，讓助教比較好處理。
>> help VQ
Usage: VQ(CS)
CS is codebook size(L)
Usage: VQ(CS)
CS is codebook size(L)
跑幾張圖來試試看好了!
source
廣告
VQ(8)
VQ(32)
VQ(128)
居然V32就已經看不太出來有什麼差別了.
這個故事告訴我們，"做影像處理的報告，乖乖的用Lenna就對了"
matlab code參考自:
http://www.wretch.cc/blog/Lak4CYUT/3518815
