[3] YU X, ZHOU Z, GAO Q, et al. Infrared image segmentation using growing immune field and clone threshold[J]. Infrared Physics & Technology, 2018, 88: 184-193.

[5] HU F, CHEN H, WANG X. An intuitionistic Kernel-based fuzzy C-means clustering algorithm with local information for power equipment image segmentation[J]. IEEE Access, 2020, 8: 4500-4514.

[6] QI C, LI Q, LIU Y, et al. Infrared image segmentation based on multi-information fused fuzzy clustering method for electrical equipment[J]. International Journal of Advanced Robotic Systems, 2020, 17(2): 1729881420909600.

[7] WEI D, WANG Z, SI L, et al. An image segmentation method based on a modified local-information weighted intuitionistic Fuzzy C-means clustering and gold-panning algorithm[J]. Engineering Applications of Artificial Intelligence, 2021, 101: 104209.

[8] BAI X, LIU M, WANG T, et al. Feature based fuzzy inference system for segmentation of low-contrast infrared ship images[J]. Applied Soft Computing, 2016, 46: 128-142.

[11] Vijayakumar S, Santhi V. Speckle noise reduction in SAR images using fuzzy inference system[J]. International Journal of Fuzzy System Applications (IJFSA), 2019, 8(4): 60-83.

[12] Arya K V. A new fuzzy rule based pixel organization scheme for optimal edge detection and impulse noise removal[J]. Multimedia Tools and Applications, 2020, 79(45): 33811-33837.

[13] BAI X, CHEN Z, ZHANG Y, et al. Infrared ship target segmentation based on spatial information improved FCM[J]. IEEE Transactions On Cybernetics, 2015, 46(12): 3259-3271.

[14] LONG J, Shelhamer E, Darrell T. Fully convolutional networks for semantic segmentation[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015: 3431-3440.