Enhanced Fuzzy Rule Based Contrast Limited Adaptive Histogram Equalization

Abstract

In recent years, tremendous research is being conducted in the field of computer technology. Our technical standards are improving day by day. Image preprocessing plays an important role in many fields of study that use computer technology. Pre-processing techniques are used to detect diseases in medical imaging. . In computer vision, images obtained with digital cameras are usually damaged by decoding errors or positive and negative pulses generated in noisy channels. When an image is digitized, it can be manipulated through a variety of image processing tasks. In image processing, noise removal is important for improving image quality, which is done by a technique called filtering. Filtering techniques and their algorithms play an important role in calculating and comparing peak signal-to-noise ratio (PSNR) values to eliminate noise and estimate noise. Image filters have three domains: spatial domain, frequency domain and fuzzy domain. Sometimes other filtering techniques appear, but when the experimental results appear, false alarm rates sometimes appear, but now removing noise from the original image is still a problem for researchers. The purpose of this white paper is to enhance the image based on fuzzy powerful preprocessing techniques and related latest work. Finally, analyze the experimental results through performance evaluation.