REVIEW OF GAMMA CORRECTION TECHNIQUES IN DIGITAL IMAGING

Abstract

Gamma correction is a crucial process in digital imaging systems, aiming to compensate for the nonlinear relationship between input signal and luminance output. This paper provides a comprehensive review of various gamma correction techniques employed in digital imaging systems. It covers both traditional methods and recent advancements, outlining their principles, advantages, and limitations. The review encompasses techniques such as power-law gamma correction, piecewise gamma correction, and adaptive gamma correction. Furthermore, it discusses the influence of gamma correction on image quality metrics, color reproduction, and perception. The paper also explores the challenges and future directions in gamma correction research, including the development of real-time adaptive algorithms and integration with machine learning approaches. Overall, this review serves as a valuable resource for researchers, engineers, and practitioners in the field of digital imaging systems, offering insights into the current state-of-the-art techniques and potential avenues for further advancements.