References

INFRARED IMAGE SEGMENTATION BASED ON LOCAL STATISTICAL ACTIVE CONTOUR MODEL


[1] N. Ning, L. Zhang, D. Zhang et al., Interactive image segmentation by maximal similarity based region merging, Pattern Recognition 43(2) (2010), 445-456.

[2] Y. Boykov and V. Kolmogorov, An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis & Machine Intelligence 26(9) (2004), 1124-1137.

[3] J. Shi and J. Malik, Normalized cuts and image segmentation, IEEE Transactions on Pattern Analysis & Machine Intelligence 22(8) (2000), 888-905.

[4] L. A. Vese and T. F. Chan, A multiphase level set framework for image segmentation using the Mumford and Shah model, International Journal of Computer Vision 50(3) (2002), 271-293.

[5] K. Zhang, L. Zhang, H. Song et al., Active contours with selective local or global segmentation: A new formulation and level set method, Image & Vision Computing 28(4) (2010), 668-676.

[6] R. Guillemaud and M. Brady, Estimating the bias field of MR images, Medical Imaging IEEE Transactions on 16(3) (1997), 238-251.

[7] S. C. Zhu and A. Yuille, Region competition: Unifying snakes region growing and Bayes/MDL for multi-band image segmentation, IEEE Transactions on Pattern Analysis & Machine Intelligence 18(9) (1996), 884-900.

[8] Xin Qi, Pengfei Li, Shuaiqi Liu et al., Research on the target and interference adhesion problem in the infrared image segmentation, International Journal of Applied Mathematics and Machine Learning 5(1) (2016), 15-24.