Matlab image processing issue

clc
clear
close all
rgb = imread('ninjagreen.jpg');
rgb=double(rgb)/255;
inds=((rgb(:,:,2)<=.58));
rgb(:,:,1)=rgb(:,:,1).*inds;
rgb(:,:,2)=rgb(:,:,2).*inds;
rgb(:,:,3)=rgb(:,:,3).*inds;
image(rgb)
red=rgb(:,:,1);
green=rgb(:,:,2);
blue=rgb(:,:,3);
redin=find(red~=0);
greenin=find(green~=0);
bluein=find(blue~=0);
forest=imread('forest.jpg');
forest=double(forest)/255;
forest_R=forest(:,:,1);
forest_G=forest(:,:,2);
forest_B=forest(:,:,3);
forest_R(redin)=red(redin);
forest_G(greenin)=green(greenin);
forest_B(bluein)=blue(bluein);
forest(:,:,1)=forest_R;
forest(:,:,2)=forest_G;
forest(:,:,3)=forest_B;
image(forest)

close all; clear all; clc;

% --- Load NINJA image ---
rgb = imread('ninjagreen.jpg');
rgb = double(rgb)/255;

% Blacken all pixels with green > 0.58
inds = rgb(:,:,2) <= .58;
rgb(:,:,1) = rgb(:,:,1).*inds;
rgb(:,:,2) = rgb(:,:,2).*inds;
rgb(:,:,3) = rgb(:,:,3).*inds;

% Display modified image
image(rgb);

% Extract red, green and blue components
red = rgb(:,:,1);
green = rgb(:,:,2);
blue = rgb(:,:,3);

% Get indices of pixels with non-zero r, g and b
redin = find(red~=0);
greenin = find(green~=0);
bluein = find(blue~=0);


% --- Load FOREST image ---
forest = imread('forest.jpg');
forest = double(forest)/255;

% Extract red, green and blue components
forest_R = forest(:,:,1);
forest_G = forest(:,:,2);
forest_B = forest(:,:,3);

% ??? Index the forest image with ninja image's non-zero r, g and b ??? 
forest_R(redin) = red(redin);
forest_G(greenin) = green(greenin);
forest_B(bluein) = blue(bluein);

% Copy results back to image data
forest(:,:,1) = forest_R;
forest(:,:,2) = forest_G;
forest(:,:,3) = forest_B;

% Display modified image
image(forest)

a = vision.ImageDataTypeConverter; %creates the object converts the input image to a single precision data type.
b = vision.ColorSpaceConverter('Conversion','RGB to intensity');
leftI3 = step(a,imread('venusl.ppm')); % step = step response of dynamic system
leftI = step(b,leftI3);
rightI3 = step(a,imread('venusr.ppm'));
rightI = step(b,rightI3);

%*******************************************************************Basic_Block_Matching******************************************************************************************************
Dbasic = zeros(size(leftI), 'single');
disparityRange = 30;
% Selects (2*halfBlockSize+1)-by-(2*halfBlockSize+1) block
halfBlockSize = 3;
blockSize = 2*halfBlockSize+1; %7X7 block
% Allocate space for all template matcher System objects.
tmats = cell(blockSize);

% Initialize progress bar
hWaitBar = waitbar(0, 'Performing basic block matching...');
nRowsLeft = size(leftI, 1); 

% Scan over all rows.
for m=1:nRowsLeft
    % Set min/max row bounds for image block.
    minr = max(1,m-halfBlockSize);
    maxr = min(nRowsLeft,m+halfBlockSize);
    % Scan over all columns.
    for n=1:size(leftI,2)
        minc = max(1,n-halfBlockSize);
        maxc = min(size(leftI,2),n+halfBlockSize);
        % Compute disparity bounds.
        mind = max( -disparityRange, 1-minc );
        maxd = min( disparityRange, size(leftI,2)-maxc );

        % Construct template and region of interest.
        template = rightI(minr:maxr,minc:maxc);
        templateCenter = floor((size(template)+1)/2);
        roi = [minc+templateCenter(2)+mind-1 ...
               minr+templateCenter(1)-1 ...
               maxd-mind+1 1];
        % Lookup proper TemplateMatcher object; create if empty.
        if isempty(tmats{size(template,1),size(template,2)})
            tmats{size(template,1),size(template,2)} = ...
                vision.TemplateMatcher('ROIInputPort',true);
        end
        thisTemplateMatcher = tmats{size(template,1),size(template,2)};

        % Run TemplateMatcher object.
        loc = step(thisTemplateMatcher, leftI, template, roi);
        Dbasic(m,n) = loc(1) - roi(1) + mind;
    end
    waitbar(m/nRowsLeft,hWaitBar);
end

close(hWaitBar);

figure(3), clf;
imshow(Dbasic,[]), axis image, colormap('jet'), colorbar;
caxis([0 disparityRange]);
title('Depth map from basic block matching');

%********************************************************************************************************************************