What does Fuzzy Image Processing mean?

Fuzzy image processing is not a unique theory. It is a collection of different fuzzy approaches to image processing. Nevertheless, the following definition can be regraded as an attempt to determine the boundaries:

Fuzzy image processing is the collection of all approaches that understand, represent and process the images, their segments and features as fuzzy sets. The representation and processing depend on the selected fuzzy technique and on the problem to be solved.
(From: Tizhoosh, Fuzzy Image Processing, Springer, 1997)

Fuzzy image processing has three main stages: image fuzzification, modification of membership values, and, if necessary, image defuzzification (see Fig.1.).

Fig. 1. The general structure of fuzzy image processing.

The fuzzification and defuzzification steps are due to the fact that we do not possess fuzzy hardware. Therefore, the coding of image data (fuzzification) and decoding of the results (defuzzification) are steps that make possible to process images with fuzzy techniques. The main power of fuzzy image processing is in the middle step (modification of membership values, see Fig.2). After the image data are transforemd from gray-level plane to the membership plane (fuzzification), appropriate fuzzy techniques modify the membership values. This can be a fuzzy clustering, a fuzzy rule-based approach, a fuzzy integration approach and so on.

Fig.2. Steps of fuzzy image processing.
(Adapted from: Tizhoosh, Fuzzy Image Processing, © CopyRight Springer,1997)