基于显著性自适应权重图的红外可见光图像融合  被引量:1

Infrared and Visible Image Fusion Based on Saliency Adaptive Weight Map

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作  者:丁海洋 董明利[1,2,3] 刘陈华 陆熙田 郭晨彤 Ding Haiyang;Dong Mingli;Liu Chenhua;Lu Xitian;Guo Chentong(Key Laboratory of Optoelectronic Measurement Technology and Instrument,Ministry of Education,School of Instrument Science and Opto-Electronics Engineering,Beijing Information Science&Technology University,Beijing 100192,China;Beijing Laboratory of Optical Fiber Sensing and System,Beijing Information Science&Technology University,Beijing 100016,China;Guangzhou Nansha Intelligent Photonic Sensing Research Institute,Guangzhou 511462,Guangdong,China)

机构地区:[1]北京信息科技大学仪器科学与光电工程学院光电测试技术及仪器教育部重点实验室,北京100192 [2]北京信息科技大学光纤传感与系统北京实验室,北京100016 [3]广州南沙光子感知技术研究院,广东广州511462

出  处:《激光与光电子学进展》2024年第10期388-395,共8页Laser & Optoelectronics Progress

基  金:北京学者计划研究项目(BJXZ2021-012-00046)。

摘  要:为改善现有融合策略对源图像信息利用不够充分的问题,利用滚动引导滤波器和各向异性扩散来提取基础层和细节层,对获取的基础层和细节层分别使用视觉显著映射和权重图构建的方法进行融合,然后添加某一权重将融合后的基础层与细节层图像融合为最终图像。基于公开数据集的多个场景进行方法实验验证。实验结果表明,相比其他方法,所提方法得到的融合结果具有更好的对比度,在保持图像像素强度均匀分布的前提下在边缘细节处保留了丰富的纹理特征,具有更好的视觉效果和融合精度,同时在平均梯度、信息熵、空间频率等指标上取得了显著的进步。To solve the problem of insufficient use of source image information by existing fusion methods,a method is proposed using rolling guided filter and anisotropic diffusion to extract the base and detail layers of an image,respectively.These layers were then fused using visual saliency mapping and weight map construction,and a certain weight was added to merge the fused layers into the final image.The proposed method was tested and verified using several scenes from an open dataset.The experimental results show that the final images obtained using the proposed method exhibit better contrast,retain richer texture features at edge details,and maintain a uniform image pixel intensity distribution;furthermore,the visual effects and fusion accuracy of the final images are better than other existing fusion methods.Moreover,significant progress has been made in indicators,such as average gradient,information entropy,and spatial frequency.

关 键 词:图像融合 红外与可见光图像 视觉显著映射 各向异性扩散 权重图构建 

分 类 号:TP391[自动化与计算机技术—计算机应用技术]

 

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