Image Processing Reference
Fig. 4.15 The effect of histogram stretching and histogram equalization on an input image with
both very high and very low pixel values
Fig. 4.16 An example of thresholding. Notice that it is impossible to define a perfect silhouette
with the thresholding algorithm. This is in general the case
One of the most fundamental point processing operations is thresholding . Thresh-
olding is the special case when f 1 = f 2 in Eq. 4.11 . Mathematically this is unde-
fined, but in practice it simply means that all input values below f 1 are mapped to
zero in the output and all input values above f 1 are mapped to 255 in the output.
This means that we will only have completely black and completely white pixel
values in the output image. Such an image is denoted a binary image , see Fig. 4.16 ,
and this representation of an object is denoted the silhouette of the object.