How to create excel sheet for the following code

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this is the code
i have converted an image into six faces(top, back, front,left, right, =bottom) for my preprocessing
1.now i need to write a loop for all faces and i need to save them seperately in the following format ( top_msss.jpg) for other faces too
2.i need to create an ecxel file for computation of entropy in each face
rows as (reference image, rating_2, rating_2, rating_3, rating_4, rating_5} and columns as (top_entropy, bottom_entropy, left_entropy, right entropy, back_entropy,front entropy_
after computation , entropy valued need to stored in excel sheet
pleasr help me as i am new to matlab
%---------------------------------------------------------
clear all; close all;
inputfilename = 'back_1.jpg';
img = imread(inputfilename);%Provide input image path
dim = size(img);
width = dim(2);height = dim(1);
gfrgb = imfilter(img, fspecial('gaussian', 3, 3), 'symmetric', 'conv');
%---------------------------------------------------------
% Perform sRGB to CIE Lab color space conversion (using D65)
%---------------------------------------------------------
cform = makecform('srgb2lab', 'AdaptedWhitePoint', whitepoint('d65'));
lab = applycform(gfrgb,cform);
l = double(lab(:,:,1));
a = double(lab(:,:,2));
b = double(lab(:,:,3));
%[l a b] = RGB2Lab(gfrgb(:,:,1),gfrgb(:,:,2), gfrgb(:,:,3));
%---------------------------------------------------------
% Create integral images
%---------------------------------------------------------
li = cumsum(cumsum(l,2));
ai = cumsum(cumsum(a,2));
bi = cumsum(cumsum(b,2));
%---------------------------------------------------------
% Compute Lab average values (note that in the paper this
% averages are found from the unblurred original image, but
% the results are quite similar)
%---------------------------------------------------------
sm = zeros(height, width);
sm2 = zeros(height, width);
for j = 1:height
yo = min(j, height-j);
y1 = max(1,j-yo); y2 = min(j+yo,height);
for k = 1:width
xo = min(k,width-k);
x1 = max(1,k-xo); x2 = min(k+xo,width);
invarea = 1.0/((y2-y1+1)*(x2-x1+1));
lm = iisum(li,x1,y1,x2,y2)*invarea;
am = iisum(ai,x1,y1,x2,y2)*invarea;
bm = iisum(bi,x1,y1,x2,y2)*invarea;
%---------------------------------------------------------
% Compute the saliency map
%---------------------------------------------------------
sm(j,k) = (l(j,k)-lm).^2 + (a(j,k)-am).^2 + (b(j,k)-bm).^2;
end
end
figure()
imshow(sm,[]);
back_entropy=entropy(sm)
%---------------------------------------------------------
  2 Commenti
KALYAN ACHARJYA
KALYAN ACHARJYA il 16 Feb 2021
It is easy to answer if the question is asked for one specific issue at a time with sample data/examples/code.

Accedi per commentare.

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