Thresholding - select pixels with given values to produce binary image
Adaptive Thresholding - like Thresholding except choose values locally
Contrast Stretching - spreading out graylevel distribution
Histogram Equalization - general method of modifying intensity distribution
Logarithm Operator - reducing contrast of brighter regions
Exponential/`Raise to Power' Operator - enhancing contrast of
brighter regions
Single-point processing is a simple method of 
image enhancement.
This technique determines a pixel value in the enhanced image dependent only on the value of the corresponding pixel in the input image.
The process can be described with the mapping function
where r and s are the pixel values in the input and output images, respectively. The form of the mapping function M determines the effect of the operation. It can be previously defined in an ad-hoc manner, as for thresholding or gamma correction, or it can be computed from the input image, as for histogram equalization. For example, a simple mapping function is defined by the thresholding operator:
The corresponding graph is shown in Figure 1.
Figure 1 Graylevel transformation function for thresholding.
Point operators are also known as
LUT-transformations, because the
mapping function, in the case of a discrete image, can be implemented
in a look-up table (LUT).
A subgroup of the point processors is the set of
anamorphosis operators.
This notion describes all point operators with a strictly increasing or decreasing mapping function.
Examples include the logarithm operator, exponential operator and contrast stretching, to name just a few.
An operator where M changes over the image is adaptive thresholding. This is not a pure point operation anymore, because the mapping function, and therefore the output pixel value, depends on the local neighborhood of a pixel.
©2003 R. Fisher, S. Perkins,
A. Walker and E. Wolfart.
