You can use the std function in MATLAB to calculate the standard deviation of each pixel along the band dimension. Here is the modified code:
% Load the image
img1 = imread('your_image_file.tif');
% Extract the second band
LS_NIRv2 = squeeze(double(img1(:, 2, :)));
% Calculate the standard deviation of each pixel along the band dimension
std_image = std(LS_NIRv2, [], 2);
% Reshape the standard deviation image to the original size
std_image = reshape(std_image, size(LS_NIRv2, 1), size(LS_NIRv2, 3));
% Display the standard deviation image
imagesc(std_image);
colorbar;
Here, the std function is applied along the second dimension (2) of the LS_NIRv2 matrix, which corresponds to the band dimension. The [] argument indicates that the standard deviation should be calculated over all elements in the band dimension. The resulting standard deviation vector is then reshaped to the original image size using the reshape function.
The resulting std_image matrix contains the standard deviation of each pixel along the band dimension. You can display this image using the imagesc function and add a colorbar to show the standard deviation values.
