Improved CLAHE Algorithm Based on Independent Component Analysis

This paper introduces an advanced image enhancement algorithm that integrates Independent Component Analysis (ICA) with Contrast Limited Adaptive Histogram Equalization (CLAHE) to tackle the challenge of feature recognition in images captured by visible light imaging devices. The process begins with converting the image from two dimensions to one. Following this, ICA is applied to decompose the one-dimensional data into a separation matrix and a fusion matrix. An adaptive algorithm then refines the separation coefficients to generate new fusion coefficients, which are used to reconstruct a clearer image. The CLAHE technique is subsequently employed to clip the histogram, preventing overamplification in certain image areas and enhancing both low-and high-contrast regions. The synergy of ICA and CLAHE enhances image quality and detail preservation, leading to more accurate image segmentation and feature extraction.