P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik, Contour Detection and Hierarchical Image Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.33, pp.898-916, 2011.

Q. Wei and D. Feng, Extracting Line Features in SAR Images Through Image Edge Fields, IEEE Geoscience and Remote Sensing Letters, vol.13, pp.540-544, 2016.

Q. Wei, D. Feng, W. Zheng, and J. Zheng, Rapid Line-Extraction Method for SAR Images Based on Edge-Field, IEEE Geoscience and Remote Sensing Letters, vol.14, pp.1865-1869, 2017.

P. Yu, A. K. Qin, and D. A. Clausi, Unsupervised Polarimetric SAR image Segmentation and Classification Using Region Growing with Edge Penalty, IEEE Transactions on Geoscience and Remote Sensing, vol.50, pp.1302-1317, 2012.

H. Song, B. Huang, and K. Zhang, A Globally Statistical Active Contour Model for Segmentation of Oil Slick in SAR Imagery, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol.6, pp.2402-2409, 2013.

J. Lee and I. Jurkevich, Coastline Detection and Tracing in SAR images, IEEE Transactions on Geoscience and Remote Sensing, vol.28, pp.662-668, 1990.

C. Liu, Y. Xiao, and J. Yang, A Coastline Detection Method in Polarimetric SAR images Mixing the Region-Based and Edge-Based Active Contour Models, IEEE Transactions on Geoscience and Remote Sensing, vol.55, pp.3735-3747, 2017.

T. Chen, L. Chen, and Y. Su, A SAR Image Registration Method Based on Pixel Migration of Edge-Point Features, IEEE Geoscience and Remote Sensing Letters, vol.11, pp.906-910, 2014.

H. Zhang, W. Ni, W. Yan, J. Wu, and S. Li, Robust SAR image Registration Based on Edge Matching and Refined Coherent Point Drift, IEEE Geoscience and Remote Sensing Letters, vol.12, pp.2115-2119, 2015.

M. Dai, C. Peng, A. K. Chan, and D. Loguinov, Bayesian wavelet shrinkage with edge detection for SAR image despeckling, IEEE Transactions on Geoscience and Remote Sensing, vol.42, pp.1642-1648, 2004.

R. Touzi, A. Lopès, and P. Bousquet, A statistical and geometrical edge detection for SAR images, IEEE Transactions on Geoscience and Remote Sensing, vol.26, pp.764-773, 1988.

R. Fjørtoft, A. Lopès, P. Marthon, and E. Cubero-castan, An optimal multiedge detector for SAR image segmentation, IEEE Transactions on Geoscience and Remote Sensing, vol.36, pp.793-802, 1998.

P. Shui and D. Cheng, Edge Detector of SAR images Using Gaussian-Gamma-Shapped Bi-Windows, IEEE Geoscience and Remote Sensing Letters, vol.9, pp.846-850, 2012.

Q. Wei, D. Feng, and H. Xie, Edge Detector of SAR Images using Crater-Shaped Window with Edge Compensation Strategy, IEEE Geoscience and Remote Sensing Letters, vol.13, pp.38-42, 2016.

J. Canny, A Computational Approach to Edge Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, issue.8, pp.679-698, 1986.

P. Shui and S. Fan, SAR Image Edge Detection Robust to Isolated Strong Scatterers Using Anisotropic Morphological Directional Ratio Test, IEEE Access, vol.6, pp.37-272, 2018.

G. Bertasius, J. Shi, and L. Torresani, Deepedge: A multi-scale bifurcated deep network for top-down contour detection, 2015 IEEE Conference on Computer Vision and Pattern Recognition, pp.4380-4389, 2015.

W. Shen, X. Wang, Y. Wang, X. Bai, and Z. Zhang, DeepContour: A deep convolutional feature learned by positive-sharing loss for contour detection, 2015 IEEE Conference on Computer Vision and Pattern Recognition, pp.3982-3991, 2015.

S. Xie and Z. Tu, Holistically nested Edge Detection, 2015 IEEE International Conference on Computer Vision, pp.1395-1403, 2015.

, Holistically-Nested Edge Detection, International Journal of Computer Vision, vol.125, pp.3-18, 2017.

, GRHED

, 14: Comparison of different methods in a 1-look real SAR image (Leystad, Sentinel 1). The size of the image are 1024 × 3072 pixels

J. Yang, B. Price, S. Cohen, H. Lee, and M. Yang, Object Contour Detection with a Fully Convolutional Encoder-Decoder Network, 2016 IEEE Conference on Computer Vision and Pattern Recognition, pp.193-202, 2016.

D. Xu, W. Ouyang, X. Mameda-pineda, E. Ricci, X. Wang et al., Learning Deep Structured Multi-Scale Features using Attention-Gated CRFs for Contour Prediction, 2017 Conferece on Neural Information Processing Systems, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01646112

Y. Liu, M. Cheng, X. Hu, K. Wang, and X. Bai, Richer Convolutioonal Features for Edge Detection, 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017.

Y. Liu, M. Cheng, X. Hu, J. Bien, L. Zhang et al., Richer Convolutional Features for Edge Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.41, pp.1939-1946, 2019.

J. Kittler, On the accuracy of the Sobel edge detector, Image and Vision Computing, vol.1, pp.37-42, 1983.

S. Konishi, A. L. Yuille, J. M. Coughlan, and S. Zhu, Statistical edge detection: Learning and Evaluating Edge Cues, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.25, pp.57-74, 2003.

D. R. Martin, C. Charless, J. Fowlkes, and . Malik, Learning to detect natural image boundaries using local brightness, color, and texture cues, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.26, pp.530-549, 2004.

P. Dollar and C. Zitnick, Fast Edge Detection Using Structured Forests, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, pp.1558-1570, 2015.

, GRHED

, 15: Comparison of different methods in a 1-look real SAR image, The size of the image are 2048 × 2048 pixels

F. Dellinger, J. Delon, Y. Gousseau, J. Michel, and F. Tupin, SAR-SIFT: A SIFT-Like Algorithm for SAR Images, IEEE Transactions on Geoscience and Remote Sensing, vol.53, pp.453-466, 2015.
URL : https://hal.archives-ouvertes.fr/hal-00831763

J. Long, E. Shelhamer, and T. Darrel, Fully convolutional networks for semantic segmentation, 2015 IEEE Conference on Computer Vision and Pattern Recognition, pp.3431-3440, 2015.

E. Shelhamer, J. Long, and T. Darrell, Fully Convolutional Networks for Semantic Segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.39, pp.640-651, 2017.

K. Simonyan and A. Zisserman, Very Deep Convolutional Networks for Large-Scale Image Recognition, International Conference on Learning Representations, 2015.

C. Lee, S. Xie, P. Gallagher, Z. Zhang, and Z. Tu, Deeply-supervised nets, International Conference on Artificial Intelligence and Statistics (AISTATS), 2015.

J. Goodman, Statistical properties of laser speckle patterns, Laser Speckle and Related Phenomena, issue.2, 1975.

K. He, X. Zhang, S. Ren, and J. Sun, Deep Residual Learning for Image Recognition, IEEE Conference on Computer Vision and Pattern Recognition, 2016.

C. Liu, R. Abergel, Y. Gousseau, and F. Tupin, LSDSAR, a Markovian a contrario framework for line segment detection in SAR images, Pattern Recognition, vol.98, 2020.
URL : https://hal.archives-ouvertes.fr/hal-01827482