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Image compression huffman coding

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lavanya vs
lavanya vs on 29 Apr 2019
Commented: Walter Roberson on 12 Jan 2020
%clearing all variableas and screen
clear all;
close all;
clc;
%Reading image
a=imread('jpeg-image-compression-1-638.JPG');
figure,imshow(a)
%converting an image to grayscale
I=rgb2gray(a);
%size of the image
[m,n]=size(I);
Totalcount=m*n;
%variables using to find the probability
cnt=1;
sigma=0;
%computing the cumulative probability.
for i=0:255
k=I==i;
count(cnt)=sum(k(:))
%pro array is having the probabilities
pro(cnt)=count(cnt)/Totalcount;
sigma=sigma+pro(cnt);
cumpro(cnt)=sigma;
cnt=cnt+1;
end;
%Symbols for an image
symbols = [0:255];
%Huffman code Dictionary
dict = huffmandict(symbols,pro);
%function which converts array to vector
vec_size = 1;
for p = 1:m
for q = 1:n
newvec(vec_size) = I(p,q);
vec_size = vec_size+1;
end
end
%Huffman Encodig
hcode = huffmanenco(newvec,dict);
%Huffman Decoding
dhsig1 = huffmandeco(hcode,dict);
%convertign dhsig1 double to dhsig uint8
dhsig = uint8(dhsig1);
%vector to array conversion
dec_row=sqrt(length(dhsig));
dec_col=dec_row;
%variables using to convert vector 2 array
arr_row = 1;
arr_col = 1;
vec_si = 1;
for x = 1:m
for y = 1:n
back(x,y)=dhsig(vec_si);
arr_col = arr_col+1;
vec_si = vec_si + 1;
end
arr_row = arr_row+1;
end
%converting image from grayscale to rgb
[deco, map] = gray2ind(back,256);
RGB = ind2rgb(deco,map);
imwrite(RGB,'decoded.JPG');
%end of the huffman coding
This code works fine but the image decoded is grey in colour. I cannot find anything wrong in it please help

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Answers (1)

Abdel Rahman Bekawi
Abdel Rahman Bekawi on 11 Jan 2020
Edited: Abdel Rahman Bekawi on 12 Jan 2020
well done, your code is great!
however, the thing that makes this logical error is that your map channels are equal to each other, hence you will get grayed scale image as well, so to overcome this issue, I recommend you work with indexed images.
% try the following
[indexed, colormap] = rgb2ind(rgbimage, number_of_colors);
% do all the processing on this indexed format and then at the end
RGB = ind2rgb(back, colormap);
% by this you should get a compressed colored image
I hope this helps!

  1 Comment

Walter Roberson
Walter Roberson on 12 Jan 2020
Note that if you are calculating compression efficiency or are expecting to be able to save the compressed image and restore it at a later time, then you should also be storing the rgb table and the Huffman dictionary

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