基于Schatten-p LatLRR的电力设备红外与可见光图像融合  

Fusion of infrared and visible light images of power equipment based on Schatten-p LatLRR

作　　者：史文云 任晓明[1] 颜楠楠 SHI Wenyun;REN Xiaoming;YAN Nannan(School of Electrical Engineering,Shanghai University of Electrical Engineering,Shanghai 201306,China;Huadong Electric Power Experimental&Research Institute Co.Ltd.,Shanghai 200437,China;Institute of Brain Intelligence Science and Technology,Fudan University,Shanghai 200433,China)

机构地区：[1]上海电机学院电气学院,上海201306 [2]华东电力试验研究院有限公司,上海200437 [3]复旦大学类脑智能科学与技术研究院,上海200433

出　　处：《激光技术》2025年第1期67-73,共7页Laser Technology

基　　金：上海电力公司科技创新智能感知专题基金资助项目(520940230015)。

摘　　要：为了解决潜在低秩表示(LatLRR)方法中使用的核函数可能导致的对秩函数逼近出现偏差问题,采用基于Schatten-p范数与潜在低秩分解的方法,进行了理论分析和实验验证。通过中值滤波方法对图像去噪,利用基于Schatten-p范数和LatLRR的图像分解方法,将图像分解为低秩部分与显著部分;采用算数平均策略融合红外与可见光的低秩部分,采用求和策略融合红外与可见光图像的显著部分;最终采用求和策略融合已融合好的低秩部分与显著部分,得到兼具清晰的纹理信息和显著的热故障信息的红外与可见光融合图像。结果表明,最佳融合效果的p值为0.6,在7种算法中有最好的融合性能。该方法能够有效地捕捉电力系统红外与可见光源图像中丰富的整体结构和局部结构信息。In order to address the potential deviation in rank function approximation caused by the kernel function used in the latent low-rank representation(LatLRR)method,an approach based on Schatten-p norm and latent low-rank decomposition was proposed.Theoretical analysis and experimental validation were conducted using this method.The images were first denoised using a median filtering method.The images were decomposed into low-rank and salient parts using the Schatten-p norm-based latent low-rank decomposition method combined with LatLRR.Then,an arithmetic mean strategy was employed to fuse the low-rank parts of the infrared and visible light images,while a summation strategy was used to fuse their salient parts.Finally,a summation strategy was applied to fuse the already merged low-rank and salient parts,resulting in fused infrared and visible light images with clear texture information and prominent thermal fault information.Through qualitative and quantitative experimental analysis,a p-value of 0.6 was determined to achieve the optimal fusion effect,and the proposed method outperformed seven other algorithms in fusion performance comparison.Through this approach,rich structural information at both global and local levels in infrared and visible light source images of power systems can be effectively captured.

关 键 词：图像处理 潜在低秩表示 Schatten-p范数 中值滤波 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]