A reliable way to check if the image is a gray scale

Question

I am currently working on one use case where I need to determine if a Gray Scale or RGB image is loaded. I found several ways to identify this, but I'm not sure if they are reliable and can be used together to confirm that the image is grayed out or not.

Part 1: read the image and get NumberDataElements using Raster.

BufferedImage image = ImageIO.read(file);
        Raster ras = image.getRaster();
        int elem = ras.getNumDataElements();

I noticed that elem is "1" in some cases, but not all.

Part 2: Check the RGB value for each pixel. If the values ​​of R, G, B coincide with the specified pixel.

BufferedImage image = ImageIO.read(file);
        Raster ras = image.getRaster();

        //Number of Color elements
        int elem = ras.getNumDataElements();

        int width = image.getWidth();
        int height = image.getHeight();

        int pixel,red, green, blue;

        for (int i = 0; i < width; i++)
            for (int j = 0; j < height; j++) {
                //scan through each pixel
                pixel = image.getRGB(i, j);
                red = (pixel >> 16) & 0xff;
                green = (pixel >> 8) & 0xff;
                blue = (pixel) & 0xff;

                //check if R=G=B
                if (red != green || green != blue ) {
                    flag = true;
                    break;
                }


            }

Here I check the values ​​of R, G, B are the same for any given pixel, and this behavior is consistent across all pixels.

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Answer 1

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BufferedImage image = ImageIO.read(file);
        Raster ras = image.getRaster();

        //Number of Color elements
        int elem = ras.getNumDataElements();

        int width = image.getWidth();
        int height = image.getHeight();

        int pixel,red, green, blue;

        for (int i = 0; i < width; i++)
            for (int j = 0; j < height; j++) {
                //scan through each pixel
                pixel = image.getRGB(i, j);
                red = (pixel >> 16) & 0xff;
                green = (pixel >> 8) & 0xff;
                blue = (pixel) & 0xff;

                //check if R=G=B
                if (red != green || green != blue ) {
                    flag = true;
                    break;
                }


            }

Answer 2

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Answer 3

if (flag) { break; } .

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Answer 4

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R = G = B. , , , false.

public static boolean isGreyscale(BufferedImage image)
{
    int pixel,red, green, blue;
    for (int i = 0; i < width; i++)
    {
        for (int j = 0; j < height; j++) 
        {
            pixel = image.getRGB(i, j);
            red = (pixel >> 16) & 0xff;
            green = (pixel >> 8) & 0xff;
            blue = (pixel) & 0xff;
            if (red != green || green != blue ) return false;
        }
    }
    return true;
}

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Answer 5

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To check if your encoding is grayscale, I suggest the following test:

int type = image.getColorModel().getColorSpace().getType();
boolean grayscale = (type==ColorSpace.TYPE_GRAY || type==ColorSpace.CS_GRAY);

To do this, you will need to import the ColorModel and ColorSpace classes from java.awt.imageand java.awt.color.

You can also find out if or image.getType()matters .BufferedImage.TYPE_BYTE_GRAYBufferedImage.TYPE_USHORT_GRAY

Answer 6

Here is a very simple way:

• Check image type
• Check Channel Image Number
• Check pixel values.

Here is the code

boolean isGrayScale(BufferedImage image)
    {
    // Test the type
    if ( image.getType() == BufferedImage.TYPE_BYTE_GRAY ) return true ;
    if ( image.getType() == BufferedImage.TYPE_USHORT_GRAY ) return true ;
    // Test the number of channels / bands
    if ( image.getRaster().getNumBands() == 1 ) return true ; // Single channel => gray scale

    // Multi-channels image; then you have to test the color for each pixel.
    for (int y=0 ; y < image.getHeight() ; y++)
    for (int x=0 ; x < image.getWidth() ; x++)
        for (int c=1 ; c < image.getRaster().getNumBands() ; c++)
            if ( image.getRaster().getSample(x, y, c-1) != image.getRaster().getSample(x, y, c) ) return false ;

    return true ;
    }