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Wrapping and Saturation

If an image is represented in a byte or integer pixel format, the maximum pixel value is limited by the number of bits used for the representation, e.g. the pixel values of a 8-bit image are limited to 255.

However, many image processing operations produce output values which are likely to exceed the given maximum value. In such cases, we have to decide how to handle this pixel overflow.

One possibility is to wrap around the overflowing pixel values. This means that if a value is greater than the possible maximum, we subtract the pixel value range so that the value starts again from the possible minimum value. Figure 1 shows the mapping function for wrapping the output values of some operation into an 8-bit format.

Figure 1 Mapping function for wrapping the pixel values of an 8-bit image.

Another possibility is to set all overflowing pixels to the maximum possible values --- an effect known as saturation. The corresponding mapping function for an 8-bit image can be seen in Figure 2.

Figure 2 Mapping function for saturating an 8-bit image.

If only a few pixels in the image exceed the maximum value it is often better to apply the latter technique, especially if we use the image for display purposes. However, by setting all overflowing pixels to the same value we lose an essential amount of information. In the worst case, when all pixels exceed the maximum value, this would lead to an image of constant pixel values. Wrapping around overflowing pixel retains the differences between values. On the other hand, it might cause the problem that pixel values passing the maximum `jump' from the maximum to the minimum value. Examples for both techniques can be seen in the worksheets of various point operators.

If possible, it is easiest to change the image format, for example to float format, so that all pixel values can be represented. However, we should keep in mind that this implies an increase in processing time and memory.


©2003 R. Fisher, S. Perkins, A. Walker and E. Wolfart.

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