i found a huffman code code from matlab examples which was for strings ,,now am implementing the same with images

am getting error as Error using horzcat Dimensions of matrices being concatenated are not consistent.please anyone help

here is the complete code and the error am getting is at line % % Form Huffman Tree Data tree = [newq_str,init_str];

tree_prob = [newq_prob, init_prob]';

and input u can give any rgb image

attached the input image

actually, i wanted to take the red_channel pixels separate huffman code followed by green and blue all the three channels separately .

then apply some chaotic process on all three channel huffman coded data and then again decode it back

can you please help in implementation

thank you

% Hufmman Coding Example
%
%  By Jason Agron
% ************************
% Setup the MATLAB console
clc;
clear all;
close all;
%load tha rgb image
 rgb_image = imread('rgb1.jpg');
 % Display the original image
figure(1)
imshow(rgb_image)
title('Original rgb Image');
%%----------- RGB to grey conversion------------%%
gray_image = rgb2gray(rgb_image);
r_gray = gray_image(:,:,1);
figure(2)
imshow(r_gray)
title('red channel to  gray ');
% g_gray = gray_image(:,:,2);
% b_gray = gray_image(:,:,3);
% %convert to string
 out_r=num2str(r_gray)
% %   out_g=num2str(g_gray)
% %     out_b=num2str(b_gray)
%
% % User-Defined Input
% Define the character string
my_str = out_r;
auto_prob = 1;
% % Probability Calculation Flag
if (auto_prob == 1)
    % Automatically calculate the probability distribution
    % Get ASCII version of each character
    % Each ASCII value represents the probability of finding the character
    prob_dist = double(my_str);
else
    % Manually define the probability distribution
%     prob_dist = [10 19 30 40 50];
end
% % Encoding Bit Calculation
num_bits = ceil(log2(length(prob_dist)))
% % Display character vs. probability
disp('Character Probability:');
for i = 1:length(prob_dist)
display(strcat(my_str(i),' -->  ',num2str(prob_dist(i))));
end
total = sum(prob_dist)
% % Initialize The Encoding Array
for i = 1:length(my_str)
sorted_str{i} = my_str(i);
end
% Save initial set of symbols and probabilities for later use
init_str = sorted_str;
init_prob = prob_dist;
%
% % Huffman Encoding Process
sorted_prob = prob_dist;
rear = 1;
while (length(sorted_prob) > 1)
% Sort probs
[sorted_prob,indeces] = sort(sorted_prob,'ascend');
% Sort string based on indeces
sorted_str = sorted_str(indeces);
% Create new symbol
new_node = strcat(sorted_str(2),sorted_str(1));
new_prob = sum(sorted_prob(1:2));
% Dequeue used symbols from "old" queue
sorted_str =  sorted_str(3:length(sorted_str));
sorted_prob = sorted_prob(3:length(sorted_prob));
% Add new symbol back to "old" queue
sorted_str = [sorted_str, new_node];
sorted_prob = [sorted_prob, new_prob];
% Add new symbol to "new" queue
newq_str(rear) = new_node;
newq_prob(rear) = new_prob;
rear = rear + 1;
end
%
% % Form Huffman Tree Data
tree = [newq_str,init_str];
tree_prob = [newq_prob, init_prob]';
% Sort all tree elements
[sorted_tree_prob,indeces] = sort(tree_prob,'descend');
sorted_tree = tree(indeces);
%
% Calculate Tree Parameters
parent(1) = 0;
num_children = 2;
for i = 2:length(sorted_tree)
% Extract my symbol
me = sorted_tree{i};
% Find my parent's symbol (search until shortest match is found)
count = 1;
parent_maybe = sorted_tree{i-count};
diff = strfind(parent_maybe,me);
while (isempty(diff))
count = count + 1;
parent_maybe = sorted_tree{i-count};
diff = strfind(parent_maybe,me);
end
parent(i) = i - count;
end
% Plot the Huffman Tree
treeplot(parent);
title(strcat('Huffman Coding Tree - "',my_str,'"'));
% Console Output - Tree Symbols and Their Probabilities
display(sorted_tree)
display(sorted_tree_prob)
% Extract binary tree parameters
[xs,ys,h,s] = treelayout(parent);
% Label Tree Nodes
text(xs,ys,sorted_tree);
% Label Tree Edges
for i = 2:length(sorted_tree)
% Get my coordinate
my_x = xs(i);
my_y = ys(i);
% Get parent coordinate
parent_x = xs(parent(i));
parent_y = ys(parent(i));
% Calculate weight coordinate (midpoint)
mid_x = (my_x + parent_x)/2;
mid_y = (my_y + parent_y)/2;
% Calculate weight (positive slope = 1, negative = 0)
slope  = (parent_y - my_y)/(parent_x - my_x);
if (slope > 0)
weight(i) = 1;
else
weight(i) = 0;
end
text(mid_x,mid_y,num2str(weight(i)));
end
% Huffman Codebook Calculation
for i = 1:length(sorted_tree)
% Initialize code
code{i} = '';
% Loop until root is found
index = i;
p = parent(index);
while(p ~= 0)
% Turn weight into code symbol
w = num2str(weight(index));
% Concatenate code symbol
code{i} = strcat(w,code{i});
% Continue towards root
index = parent(index);
p = parent(index);
end
end
% Console Output - Huffman Codebook
codeBook = [sorted_tree', code']

[Jan]

We cannot run your code, because we do not have your input data. Therefore the readers must be able to recognize the problem only using your explanation. So please post the complete error message and mention, in which line the problem occurs.

I'd ask the author Jason Agron at first.

Omit the darn clear all, because it is not useful but expensive.

[Jan]

You wrote: "attached the input image" - no, there is no attached image yet. Please try it again.

[juveria fatima]

here is the input image attached

[juveria fatima]

sorry for the inconvenience actually am using matlab for the first time

i have attached the input image

the error is in line 109 i.e "tree_prob = [newq_prob , init_prob];"

*the size of newq_prob is 1*1417

the size of init_prob is 177*1418* due to different in size am getting error pls help to resolve asap

else you can run on any rgb image