How to convert a grayscale matrix to an RGB matrix in MATLAB?

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心在旅途
心在旅途 2020-12-09 12:37
rgbImage = grayImage / max(max(grayImage));

or

rgbImage = grayImage / 255;

Which of the above is right,and reason

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  • 2020-12-09 13:01

    To convert a grayscale image to an RGB image, there are two issues you have to address:

    • Grayscale images are 2-D, while RGB images are 3-D, so you have to replicate the grayscale image data three times and concatenate the three copies along a third dimension.
    • Image data can be stored in many different data types, so you have to convert them accordingly. When stored as a double data type, the image pixel values should be floating point numbers in the range of 0 to 1. When stored as a uint8 data type, the image pixel values should be integers in the range of 0 to 255. You can check the data type of an image matrix using the function class.

    Here are 3 typical conditions you might encounter:

    • To convert a uint8 or double grayscale image to an RGB image of the same data type, you can use the functions repmat or cat:

      rgbImage = repmat(grayImage,[1 1 3]);
      rgbImage = cat(3,grayImage,grayImage,grayImage);
      
    • To convert a uint8 grayscale image to a double RGB image, you should convert to double first, then scale by 255:

      rgbImage = repmat(double(grayImage)./255,[1 1 3]);
      
    • To convert a double grayscale image to a uint8 RGB image, you should scale by 255 first, then convert to uint8:

      rgbImage = repmat(uint8(255.*grayImage),[1 1 3]);
      
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  • 2020-12-09 13:08

    By definition, an RGB image has 3 channels, which implies you need a three-dimensional matrix to represent the image. So, the right answer is:

    rgbImage = repmat(255*grayImage/max(grayImage(:)),[1 1 3]);
    

    Be careful when normalizing grayImage. If grayImage is uint8 then you will lose some precision in the 255*grayImage/max(grayImage(:)) operation.

    Also, normalizing grayImage depends on the data. In your question, you used two methods:

    rgbImage = grayImage / max(max(grayImage));
    

    which normalizes the grayscale image such that the maximum value in the image is 1 and

    rgbImage = grayImage / 255;
    

    which only makes sense if the values in grayImage lie in the 0-255 range.

    So it really depends on what you want to do. But, if you want an RGB image you need to convert your single-channel matrix to a 3-channel matrix.

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