Multi-scale Guided Filter and Decision Fusion for Thermal Fault Diagnosis of Power Equipment

Jian LIANG; Zhihong HUANG; Keren ZHANG

[12] HUANG Z, ZHOU J, LI S, et al. Superpixels segmentation and low-rank matrix recovery for thermal fault diagnosis of power equip-ment[C]//IEEE 5th Conference on Energy Internet and Energy System Integration, 2021: DOI: 10.1109/EI252483.2021.9713012

[13] KANG X, ZHANG X, LI S, et al. Hyperspectral anomaly detection with attribute and edge-preserving filters[J]. IEEE Transactions on Geosci-ence and Remote Sensing, 2017, 55(10): 5600-5611.

[14] HE K, SUN J, TANG X. Guided image filtering[C]//Proc. of Processing IEEE Conference Computer Vision Pattern Recognition, 2010: 1-14.

[15] Durand F, Dorsey J. Fast bilateral filtering for the display of high-dynamic-range images[J]. ACM Transactions on Graphics, 2002, 21(3):

[16] Reed I S, YU X. Adaptive multiple-band CFAR detection of an optical pattern with unknown spectral distribution[J]. IEEE Transactions on Acoustic Speech Signal Processing, 1990, 38(10): 1760-1770.

[17] KANG X, ZHANG X, LI S, et al. Hyperspectral anomaly detection with attribute and edge-preserving filters[J]. IEEE Trans. Geosci. Remote Sens., 2017, 55(10): 5600-5611.

[18] XU Y, WU Z, LI J, et al. Anomaly detection in hyperspectral images based on low-rank and sparse representation[J]. IEEE Trans. Geosci. Remote Sens., 2016, 54(4): 1990-2000.