This paper discusses current formulations based on fuzzy-logic control concepts as applied
to the removal of impulsive noise from digital images. We also discuss the various principles …

A Gaussian membership function is proposed to fuzzify the image information in spatial
domain. We introduce a global contrast intensification operator (GINT), which contains three …

This paper presents a systematic Type-II fuzzy expert system for diagnosing the human brain
tumors (Astrocytoma tumors) using T1-weighted Magnetic Resonance Images with contrast …

In the Western world, the successful introduction of insect consumption may need
awareness of insect ingredient benefits, and consumers' anticipation of insect-based foods …

In contrast to classical image analysis methods that employ" crisp" mathematics, fuzzy set
techniques provide an elegant foundation and a set of rich methodologies for diverse image …

This paper presents a fuzzy grayscale enhancement technique for low contrast image. The
degradation of the low contrast image is mainly caused by the inadequate lighting during …

A contrast enhancement of medical images using Type II fuzzy set theory is suggested.
Fuzzy set theory considers uncertainty in the form of membership function but to have better …

An inclement dusty weather can significantly reduce the visual quality of captured images,
which consequently hampers the observation of important image details. Capturing images …

This paper presents a novel approach for the enhancement of high dynamic range color
images using fuzzy logic and modified Artificial Ant Colony System techniques. Two …

This higher-level text provides a brief introduction to advanced fuzzy set theory,
fuzzy/intuitionistic fuzzy aggregation operators, and distance/similarity measures. It covers …