IMAGE CONTRAST ENHANCEMENT METHOD BASED ON FUZZY LOGIC

Abstract

This thesis analyzes fuzzy logic-based approaches for image contrast enhancement. Brightness differences between pixels are modeled using "IF-THEN" rules. Methods for enhancing contrast, reducing noise, and detecting contours using membership functions are explored. Fuzzy singletons, fuzzy inference systems, and defuzzification processes are highlighted as key components [3]. The cited approaches offer higher accuracy compared to classical methods. However, their computational complexity may be a limitation in resource-constrained systems.