Low-light enhanced gradient transfer fusion: a collaborative optimization approach for infrared-visible image fusion
Year: 2025
Type: conference-paper
Abstract: A fusion algorithm named LLE-GTF to resolve the insufficient collaboration between conventional visible and infrared fusion (VIF) methods and low-light enhancement techniques in nighttime scenarios. The proposed LLE-GTF framework incorporates two complementary logarithmic gamma transform functions: an Enhanced Logarithmic Gamma Correction (ELGC) function for low-light amplification and a Suppressed Logarithmic Gamma Correction (SLGC) function for highlight regulation. These dual components work synergistically to achieve dynamic range compression, enhancing texture details in low-light regions while preventing saturation in highlight areas. By implementing gradient transfer fusion, the method optimally combines gradient features from enhanced visible images with radiation characteristics from infrared data. This hybrid approach significantly improves fused image quality under nocturnal high-light conditions, producing results that approximate daytime scene clarity while better aligning with human visual sensitivity.
DOI: 10.1117/12.3068595
Authors: Wei Gao, Youning Wei, Yu Zhang, Yi Shi, Peng Yang, Wei Mao
Language: English
Subfield: Media Technology
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4414145115