Hi Tevin,
To convert a 32-bit image to a uint16 image while preserving the grayscale values, you need to scale the pixel values appropriately. The goal is to map these values to the 0-65535 range, since uint16 can represent values in this range. Here is a sample code to do that:
% Read a 32-bit image. Replace 'your_image_path.png' with the actual path to your image.
% This assumes the image is stored in a format that supports 32-bit data (e.g., PNG, TIFF).
img32 = imread('your_image_path.png');
% Convert the image to double precision for processing, assuming it's not already
img32Double = double(img32);
% If your image is in a floating-point format with values ranging from 0 to 1,
% you can skip this step. If it's a 32-bit integer format, you should scale it to [0, 1]:
% img32Double = img32Double / double(intmax('uint32'));
% Scale the values from the [0, 1] range to [0, 65535] range for uint16
% Adjust this line if your original image uses a different scale
img16 = uint16(img32Double * 65535);
% Save the 16-bit image. Choose an appropriate format that supports 16-bit data.
imwrite(img16, 'your_output_image_path.tif');
You can refer to the following documentation to know more about functions used:
- imwrite: https://www.mathworks.com/help/matlab/ref/imwrite.html
- uint16: https://www.mathworks.com/help/matlab/ref/uint16.html
- imread: https://www.mathworks.com/help/matlab/ref/imread.html
Best Regards,
Abhishek Chakram
