Dr. Yang Yang Profile

Dr. Yang Yang

at China Electric Power Research Institute

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Publications (2)

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Proceedings Article | 6 August 2021 Paper

Infrared and visible image fusion algorithm for substation equipment based on NSCT and Siamese network

Yang Yang, Yu Yin, Ning Yang, Lihua Li

Proceedings Volume 11913, 1191304 (2021) https://doi.org/10.1117/12.2605018

KEYWORDS: Image fusion, Image filtering, Fusion energy, Discrete wavelet transforms, Image processing, Image quality, Linear filtering

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In order to accurately obtain the status information of substation equipment, a large number of infrared and visible images will be used in the process of equipment maintenance. Traditional image fusion methods often lose the temperature information of the image, resulting in low brightness and contrast in the fusion image; while deep learning fusion algorithm will lose some details. Therefore, this paper proposes an infrared and visible light fusion algorithm based on NSCT and Siamese network to improve the quality of fusion image. Firstly, the infrared and visible images are decomposed by NSCT; the high-frequency part and low-frequency part are fused by the fusion rule of guided filtering, and the new high-frequency subband coefficient FH and the new low-frequency subband FL are obtained; then the first fusion image is obtained by NSCT reconstruction of FH and FL; after that, the weight mapping image of the first fusion image and the infrared image is obtained by convolution network, and at the same time Laplacian pyramid is used to decompose the primary fusion image and infrared image, and Gaussian pyramid is used to decompose the weight map; finally, the primary fusion image subband, infrared image subband and weight map image subband are fused according to the local window energy fusion method, and the final image is reconstructed by Laplacian pyramid. Experiments show that the subjective and objective indicators of the fusion picture are all improved.

Proceedings Article | 6 August 2021 Paper

Research on infrared and visible image registration of substation equipment based on multi-scale Retinex and ASIFT features

Ning Yang, Yang Yang, Peng Li, Fei Gao

Proceedings Volume 11913, 1191303 (2021) https://doi.org/10.1117/12.2605000

KEYWORDS: Image processing, Visible radiation, Infrared imaging, Image registration, Infrared radiation, Image filtering, Image fusion, Gaussian filters, Cameras, Feature extraction

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Infrared and visible image registration of substation equipment is of great significance for power equipment detection and fault diagnosis. The scene of substation is complex, and the background of equipment image is usually messy, and the feature points of visible image are easy to fall on the background. The metal has good thermal conductivity, and its temperature is close to the ambient temperature. The metal part in the infrared image with metal tower as the background can not be clearly displayed, which is easy to cause the image mismatch or even unable to match. The existing registration methods such as SIFT, SURF and ASIFT are difficult to effectively solve this kind of image registration problem of substation equipment with complex background. To solve this problem, this paper proposes an infrared and visible image registration algorithm based on Multi-scale Retinex and ASIFT features. Firstly, the Multi-scale Retinex algorithm is used to separate the components representing the properties of the object in the visible image, so as to weaken the influence of the clutter background. Then, the ASIFT algorithm is used to do affine transformation to simulate the affine deformation under all parallax, and the feature points are roughly matched Finally, the random sampling consistent algorithm is added to eliminate the mismatching points. Experimental results show that the algorithm can increase the number of matching points by at least 4 times, the average matching accuracy is improved by 13%, and the average matching time is shortened by 183ms.

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