四川师范大学学报（自然科学版）2026，Vol.49Issue(2)：237-245,9.DOI:10.3969/j.issn.1001-8395.2026.02.009
融合同态滤波与注意力机制的低照图像增强算法研究
Research on Enhancement Algorithm of Low-illumination Images Integrating Homomorphic Filtering and Attention Mechanism
摘要
Abstract
Images captured under low-light conditions suffer from quality degradation,poor visibility,and edge blurring,which seriously affect the performance of images in advanced visual tasks such as target detection,recognition,and classification.A RetinexNet image enhancement algorithm that combines homomorphic filtering and attention mechanism is proposed to address these problems.The algorithm first converts the image to HSV color space,and adopts an improved RetinexNet strategy that integrates homomorphic filtering and attentional mechanism to adjust the luminance component V and enhance the contrast.Subsequently,based on the adaptive gamma correction mode,the saturation component S is adjusted to the color balance by combining the enhanced luminance intensity.Finally,the processed image is converted back to RGB space to obtain the enhanced low-light image.The experimental results show that this method can enhance the image details and contour performance,maintain a better color naturalness and improve the visual effect while significantly improving the image brightness and contrast.关键词
低照图像增强/RetinexNet算法/HSV/同态滤波/γ校正Key words
low-illumination image enhancement/RetinexNet algorithm/HSV/homomorphic filtering/γ correction分类
信息技术与安全科学引用本文复制引用
刘雨轩,罗海月,蒋滔,刘呈滢,孙艺,廖雪花..融合同态滤波与注意力机制的低照图像增强算法研究[J].四川师范大学学报（自然科学版）,2026,49(2):237-245,9.基金项目
国家社会科学基金一般项目(20BMZ092) （20BMZ092）
