This is a code for Image Compression using Huffman Coding. Could someone tell me why am I not able to calculate the entropy? And how could I go about writing creating a file which contains the compressed image ?

%clearing all variableas and screen
clear all;
close all;
clc;
%Reading image
a=imread('chair.png');
figure,imshow(a)
%converting an image to grayscale
[I, colormap] = rgb2ind(a, 256);
%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, avglen] = huffmandict(symbols,pro);
entropy = - sum (pro .* log10(pro)/log10(2))
disp(['Entropy: ' num2str(entropy)]);
disp(['Average Length: ' num2str(avglen)])
%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
RGB = ind2rgb(back, colormap);
imwrite(RGB,'decoded.png');
%end of the huffman coding

Answer 1

[Haleem Ebdul]

Instead of writing image to disk, i use figure to display image, then save as jpg. boom it give what i want, the image size is half of original

% imwrite(RGB,'decoded.png');

figure,imshow(RGB)