My previous post gave three algorithms for converting color to grayscale. This post gives more examples and details.

The image below is a screenshot from an Excel spreadsheet illustrating color values and how the convert to grayscale. The R, G, and B columns are the red, green, and blue component values of the color sample in the leftmost column. The columns labeled “Li”, “Lu”, and “Avg” are the grayscale values of the color using the lightness, luminosity, and average algorithms from the previous post.

The grayscale color samples were created by asking Excel to set the background color to (X, X, X) where X is the grayscale value. For example, the background color for the “Lu” column of the first row is (54, 54, 54) since 54 is the luminosity value for pure red.

To verify the algorithms, I converted the screen shot above to a grayscale image using GIMP. The gray cells remain unchanged because all three algorithms leave gray alone; when all three RBG values are equal, it’s clear from the formulas that the grayscale value becomes the common value. The color cells in the first column become the shade of gray predicted and hence match the column of gray cells for that algorithm.

Using lightness:

Using luminosity:

Using average:

Related post: Three algorithms for converting color to grayscale

How do you convert a color image to grayscale? If each color pixel is described by a triple (R, G, B) of intensities for red, green, and blue, how do you map that to a single number giving a grayscale value? The GIMP image software has three algorithms.

The lightness method averages the most prominent and least prominent colors: (max(R, G, B) + min(R, G, B)) / 2.

The average method simply averages the values: (R + G + B) / 3.

The luminosity method is a more sophisticated version of the average method. It also averages the values, but it forms a weighted average to account for human perception. We’re more sensitive to green than other colors, so green is weighted most heavily. The formula for luminosity is 0.21 R + 0.72 G + 0.07 B.

The example sunflower images below come from the GIMP documentation.

Original image
Lightness
Average
Luminosity

The lightness method tends to reduce contrast. The luminosity method works best overall and is the default method used if you ask GIMP to change an image from RGB to grayscale from the Image -> Mode menu. However, some images look better using one of the other algorithms. And sometimes the three methods produce very similar results.

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VectorMagic is a free online tool from the Standford University AI lab for converting bitmap images to vector formats. The image below shows an example of what you might use this tool for.

I just heard about the software and tried it out with a fairly complex image, a sample of Japanese calligraphy, and it did a beautiful job converting the image from bitmap to EPS (Encapsulated PostScript).

The software supports JPEG, GIF, PNG, BMP, and TIFF input. It supports EPS, SVG, and PNG output.

(In case you’re not familiar with graphic formats, a bitmap image is a matrix of dots. The format records what color each dot is. That works fine when an image is displayed at its original resolution. But if you make the image bigger, you just get bigger dots and things look grainy. A vector format stores the formulas for the curves that make up the image, not the dots, and computes the dots when it’s time to display the image. If you make an image larger, it computes new dots according to the formulas. Software for making bitmaps smaller is common. Software that does a good job of making bitmaps larger is rare.)

Update: VectorMagic has moved to a new domain. I’ve corrected the link above.