Fuzzy Contrast Enhancement Techniques Using Rule-Based System and Intensification Operator

Abstract

Contrast enhancement is a crucial step in digital image processing to ensure the production of high-quality images. This paper presents two distinct fuzzy techniques designed to address the nuanced concept of contrast. that utilize rule-based system and intensification operator, respectively, to handle the inherent vagueness associated with the concept of contrast. The fuzzy rule-based system calculates the intensity value of the output image based on the contrast measure (standard deviation) of the input image, thereby enabling effective contrast enhancement for low contrast images. Meanwhile, the fuzzy intensification operator aims to accentuate the differences in intensity levels within the image, thereby enhancing the contrast between various features and details. The experimental results show better image contrast is obtained using both methods. However, fuzzy rule-based approach shows more images with better quality compared to the intensification operator approach. The performance of these techniques is evaluated both visually and quantitatively.