[1] Ren J C, Hwang B, Murray P et al. Effective SAR sea ice image segmentation and touch floe separation using a combined multi-stage approach. [C]∥2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 26-31, 2015, Milan, Italy. New York: IEEE, 1040-1043(2015).

[2] Li Q L. Study on separation method of large contact ice floes in polarimetric SAR ice flow zone[D]. Dalian: Dalian Maritime University(2017).

[3] Al-amri S S, Kalyankar N V. -05-21)[2019-12-23]. https:∥arxiv., org/abs/1005, 4020(2010).

[4] Dang X Y, Wu Y M, Fan W et al. Discussion on sea ice segmentation of high resolution radar data. [C]∥2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 10-15, 2016, Beijing, China. New York: IEEE, 4861-4864(2016).

[5] Yang X Z, Clausi D A. Evaluating SAR sea ice image segmentation using edge-preserving region-based MRFs[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 5, 1383-1393(2012).

[6] Chen Q F, Koltun V. Fast MRF optimization with application to depth reconstruction. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 3914-3921(2014).

[7] Han L Y. Research on SAR image segmentation based on watershed Xi'an:[D]. Xidian University(2018).

[8] Jing Y, Liu J X, Liu Z X et al. Fast edge detection approach based on global optimization convex model and split Bregman algorithm[J]. Diagnostyka, 19, 23-29(2018).

[9] Tan W K, Li J, Xu L L et al. Semiautomated segmentation of Sentinel-1 SAR imagery for mapping sea ice in Labrador coast[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11, 1419-1432(2018).

[10] Karvonen J A. Baltic sea ice SAR segmentation and classification using modified pulse-coupled neural networks[J]. IEEE Transactions on Geoscience and Remote Sensing, 42, 1566-1574(2004).

[11] Zhang Q, Skjetne R. Image processing for identification of sea-ice floes and the floe size distributions[J]. IEEE Transactions on Geoscience and Remote Sensing, 53, 2913-2924(2015).

[12] Zhou Y, Mao A L, Huo S W et al. Salient object detection via fuzzy theory and object-level enhancement[J]. IEEE Transactions on Multimedia, 21, 74-85(2019).

[13] Achanta R, Shaji A, Smith K et al. SLIC superpixels compared to state-of-the-art superpixel methods[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34, 2274-2282(2012).

[14] Zhu W J, Liang S, Wei Y C et al. Saliency optimization from robust background detection. [C]∥2014 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2014, Columbus, OH, USA. New York: IEEE, 2814-2821(2014).

[15] Yang C, Zhang L H, Lu H C et al. Saliency detection via graph-based manifold ranking. [C]∥2013 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2013, Portland, OR, USA. New York: IEEE, 3166-3173(2013).

[16] Wei Y C, Wen F, Zhu W J et al. Geodesic saliency using background priors[M]. ∥Fitzgibbon A, Lazebnik S, Perona P, et al. Computer vision-ECCV 2012. Lecture notes in computer science. Heidelberg: Springer, 7574, 29-42(2012).

[17] Jiang H Z, Wang J D, Yuan Z J et al. Salient object detection: a discriminative regional feature integration approach. [C]∥2013 IEEE Conference on Computer Vision and Pattern Recognition, June 23-28, 2013, Portland, OR, USA. New York: IEEE, 2083-2090(2013).

[18] Sun J G, Lu H C, Liu X P. Saliency region detection based on Markov absorption probabilities[J]. IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society, 24, 1639-1649(2015).

[19] Qin Y, Lu H C, Xu Y Q et al. Saliency detection via cellular automata. [C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 7-12, 2015, Boston, MA, USA. New York: IEEE, 110-119(2015).

[20] Zhou L, Yang Z H, Zhou Z T et al. Salient region detection using diffusion process on a two-layer sparse graph[J]. IEEE Transactions on Image Processing, 26, 5882-5894(2017).