X-ray Image Enhancement Based on Gated Context Aggregation Network

This paper considered the similarity of X-ray enhancement and Dehazing tasks, then proposed a method based on Gated Context Aggregation Network (GCANet). The experimental results demonstrate that GCANet performs better than four traditional X-ray image enhancement algorithms in terms of Contrast Improvement Index (CII), Measure of Enhancement by Entropy (EME), and Entropy (ENT). It effectively enhances image contrast, recovers useful information, and preserves details in both bright and dark areas.