Image enhancement: probability versus fuzzy expert systems

Authors:
Aly El-Osery;Mo Jamshidi
Affiliations:
New Mexico Institute of Mining and Technology;University of New Mexico
Venue:
Fuzzy logic and probability applications
Year:
2002

Citing 6
Cited 0

On the color image segmentation algorithm based on the thresholding and the fuzzy C-means techniques

Pattern Recognition
A study on subjective evaluations of printed color images

International Journal of Approximate Reasoning
Fuzzy logic and control: software and hardware applications

Fuzzy logic and control: software and hardware applications
Pattern Recognition with Fuzzy Objective Function Algorithms

Pattern Recognition with Fuzzy Objective Function Algorithms
Digital Image Processing

Digital Image Processing
Computer Vision

Computer Vision

Quantified Score

Hi-index	0.00

Visualization

Abstract

The field of image enhancement is being used in various areas and disciplines. Advances in computers, microcontrollers, and digital signal processing (DSP) boards have opened new horizons to digital image processing and many avenues to the design and implementation of new innovative techniques. This chapter compares image enhancement, via modification of the probability density function of gray levels, with new techniques that involve the use of knowledge-based (fuzzy expert) systems capable of mimicking the behavior of a human expert.