Optimizing Tone Separation of Photographic Images
Tone separation is the process of reducing a continuous tone image to a set of discrete tone levels. It is usually the first step in many graphic arts techniques, for example posterization. This Demonstration shows the partition of a continuous tone photograph into four tone intervals defined by three thresholds: one for the shadows, one for the midtones, and one for the highlights. Adjust the threshold values and see the effect on the four negative or positive masks and on the composition of all four masks into a posterization. Three evenly spaced thresholds (0.25, 0.50, and 0.75) can be used, but they usually result in unbalanced fractions of black and white, forming a less pleasing composition. If we optimize the threshold values to produce equal black fractions for each separation (0.25 for the positives or 0.75 for the negatives), we get a more interesting posterization. White dust spots, caused by repeated binarization, can be removed with the new Inpaint function in Mathematica 8.
Snapshot 1: shows the thumbnail image with evenly spaced thresholds
Snapshot 2: an example of an image with very strong highlights and almost no shadows or midtones, giving poor results in the composition with evenly spaced threshold values
Snapshot 3: the same image as in Snapshot 2 but with optimized thresholds and resulting in a better composition