电气技术2025，Vol.26Issue(3)：22-29,8.
变电站低照度场景红外可见光图像融合
Infrared visible light image fusion in low light scenarios of substations
摘要
Abstract
The image acquisition of substations in low light environments can lead to problems such as low visual quality,loss of details,and low contrast,which in turn affect the subsequent detection and monitoring of equipment.A fusion method based on low light image enhancement and nonsubsampling contourlet transform(NSCT)and discrete cosine transform(DCT)technology is proposed in this paper.Firstly,adaptive image adjustment is performed on visible light images based on gamma parameters to enhance visibility.Then NSCT decomposes the image into high and low frequency coefficients.For high-frequency coefficients,edge information extraction based on Sobel operator is used,and for low-frequency coefficients,improved DCT-DFT is used for decomposition and integration.The decomposed amplitude spectrum and the phase spectrum are fused using contrast enhancement weighting and local energy optimization rule based on singular value decomposition(SVD),respectively.Finally,the fused image is obtained by NSCT inverse transformation.Three sets of images of common equipment in substations are used to compare the proposed method with other algorithms.The results show that this proposed method performs better in indicators such as average gradient,information entropy and mutual information.关键词
图像融合/低照度图像/非下采样轮廓波变换(NSCT)/离散余弦变换(DCT)/奇异值分解(SVD)Key words
image fusion/low light image/nonsubsampled contourlet transform(NSCT)/discrete cosine transform(DCT)/singular value decomposition(SVD)引用本文复制引用
赵杰,陈嘉晋..变电站低照度场景红外可见光图像融合[J].电气技术,2025,26(3):22-29,8.基金项目
省属高校科研业务费项目(2022-KYYWF-0551) （2022-KYYWF-0551）
