Medical X-Ray Image Enhancement Using Global Contrast-Limited Adaptive Histogram Equalization

TL;DR

This paper introduces G-CLAHE, a novel image enhancement technique for X-ray images that combines global and local contrast enhancement to improve diagnostic quality.

Contribution

The paper proposes G-CLAHE, a new method that integrates global histogram equalization and CLAHE to better preserve image details in medical X-ray imaging.

Findings

Significantly improves contrast and image quality of X-ray images.

Outperforms existing enhancement algorithms in preserving global and local features.

Enhances diagnostic accuracy through better image clarity.

Abstract

In medical imaging, accurate diagnosis heavily relies on effective image enhancement techniques, particularly for X-ray images. Existing methods often suffer from various challenges such as sacrificing global image characteristics over local image characteristics or vice versa. In this paper, we present a novel approach, called G-CLAHE (Global-Contrast Limited Adaptive Histogram Equalization), which perfectly suits medical imaging with a focus on X-rays. This method adapts from Global Histogram Equalization (GHE) and Contrast Limited Adaptive Histogram Equalization (CLAHE) to take both advantages and avoid weakness to preserve local and global characteristics. Experimental results show that it can significantly improve current state-of-the-art algorithms to effectively address their limitations and enhance the contrast and quality of X-ray images for diagnostic accuracy.