want to calculate std_value and mean_value

below is my coding but i dont what happend i dont get data

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img1 = imread('SCM Data.jpg');

img = (-0.18 / (-0.28 / (45.39 / double(img1) - 1)) + 1) * 5.3;

std_value = std2(img);

mean_value = mean2(img);

fprintf('standard deviation：%.2f\n', std_value);

fprintf('average value：%.2f\n', mean_value);

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by the way if i conducted calculate it will chage to

Answer 1

[Star Strider]

There are 395449 ‘Inf’ values in ‘img’ (probably the result of the subtraction in the denominator of the transformation) so those are going to produce either Inf or NaN values in the mean and standard deviation. One way to deal with that is to assign all the Inf values to be NaN and then use the new fillmissing2 function (R2020a does not have it, and I am not certain what to suggest in its absence other than perhaps fillmissing and then hope for the best, since it seems to produce the same result) on each channel of ‘img’.

Then, do the statistics —

img1 = imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1523076/image.jpeg');

img = (-0.18 / (-0.28 / (45.39 / double(img1) - 1)) + 1) * 5.3;
size(img)

ans = 1×3

755 869 3

nans = nnz(isnan(img))                                          % Check 'NaN' Values

nans = 0

infs = nnz(isinf(img))                                          % Check 'Inf' Values

infs = 395449

img(isinf(img)) = NaN;                                          % Assign 'Inf' Values To 'NaN'

imgz = zeros(size(img));

for k = 1:size(img,3)
    img(:,:,k) = fillmissing2(img(:,:,k), 'nearest');
    imgz(:,:,k) = fillmissing(img(:,:,k), 'nearest');
end

std_value = std2(img);
mean_value = mean2(img);
fprintf('standard deviation：%.2f\n', std_value);

standard deviation：46.14

fprintf('average value：%.2f\n', mean_value);

average value：29.48

std_value = std2(imgz);
mean_value = mean2(imgz);
fprintf('standard deviation：%.2f\n', std_value);

standard deviation：46.14

fprintf('average value：%.2f\n', mean_value);

average value：29.48

This uses the provided image, that includes the borders and colorbar. (I did not crop it.) You will likely get different results from your actual image (that ideally should have been provided).

.

[bozheng]

nans =

0

infs =

395449

Unrecognized function or variable 'fillmissing2'.

Error in

img(:,:,k) = fillmissing2(img(:,:,k), 'nearest');

[Star Strider]

Just use fillmissing. When I checked (included in my code), it gave the same result as fillmissing2.

img1 = imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/1523076/image.jpeg');

img = (-0.18 / (-0.28 / (45.39 / double(img1) - 1)) + 1) * 5.3;
size(img)

ans = 1×3

755 869 3

nans = nnz(isnan(img))                                          % Check 'NaN' Values

nans = 0

infs = nnz(isinf(img))                                          % Check 'Inf' Values

infs = 395449

img(isinf(img)) = NaN;                                          % Assign 'Inf' Values To 'NaN'

for k = 1:size(img,3)
    img(:,:,k) = fillmissing(img(:,:,k), 'nearest');
end

std_value = std2(img);
mean_value = mean2(img);
fprintf('standard deviation：%.2f\n', std_value);

standard deviation：47.28

fprintf('average value：%.2f\n', mean_value);

average value：30.55

.

Answer 2

[Sulaymon Eshkabilov]

Here is the correct code:

img1 = imread('ALPS.jpg');
figure
imshow(img1); title('Original Image')

std_value1 = std2(img1);
mean_value1 = mean2(img1);
fprintf('Original Image: \n')

Original Image: 

fprintf('standard deviation：%.5f\n', std_value1);

standard deviation：63.19555

fprintf('average value：%.5f\n', mean_value1);

average value：101.80412

img2 = (-0.18./(-0.28/(45.39./(img1)- 1))+1) * 5.3;
std_value2 = std2(img2);
mean_value2 = mean2(img2);
fprintf('Changed Image: \n')

Changed Image: 

fprintf('standard deviation：%.5f\n', std_value2);

standard deviation：0.00000

fprintf('average value：%.5f\n', mean_value2);

average value：5.00000

figure
% See why std2 is giving '0'
imshow(img2), title('Changed Image')