Futuristic Hybrid Image Enhancement Using Fuzzy and Cubic Interpolation Methods

Abstract

Contrast enhancement is a significant image processing operation to improve the images taken with a poor camera or poor environmental conditions. Contrast enhancement can be completed through a spatial domain by mapping the original intensity level to an enhanced intensity level. However, most methods are based on applying complex mathematical interpolation to find the enhanced intensity level. We propose a hybrid fuzzy logic-based intensity mapping along with cubic interpolation method to find the best intensity level mapping. The fuzzy interpolation reduces complexity and enhances image intensity as a local optimization method, while cubic interpolation smooths the image as a global optimization method. We run several experiments using a benchmark dataset, and we show an enhancement of our integrated model with more than 52% over spline interpolation and 8% over fuzzy interpolation.