, LSDSAR, contrast, vol.1, issue.2

. Grhed-+-hough, , vol.1

, LSDSAR, contrast, vol.1, issue.3

. Grhed-+-hough, , vol.1

, LSDSAR, contrast, vol.1, issue.4

. Grhed-+-hough, , vol.1

, LSDSAR, contrast, vol.1, issue.5

. Grhed-+-hough, , vol.1

, 14 -Comparison of LSDSAR and GRHED + Hough transform in four 1-look synthetic edge images, vol.10

E. J. Bibliographie, R. Almazan, Y. Tal, J. H. Qian, and . Elder, Mcmlsd : A dynamic programming approach to line segment detection, 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017.

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.

A. Arnold-bos, A. Khenchaf, and A. Martin, An evaluation of current ship wake detection algorithms in SAR images, Caractérisation du milieu marin, 2006.

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.

A. Bonci, T. Leo, and S. Longhi, A bayesian approach to the hough transform for line detection, IEEE Transactions on Systems, Man, and Cybernetics, vol.35, pp.945-955, 2005.

K. Bowyer, C. Kranenburg, and S. Dougherty, Edge detector evaluation using empirical roc curves, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol.1, p.359, 1999.

J. Canny, A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.8-679, 1986.

J. Chanussot, G. Mauris, and P. Lambert, Fuzzy fusion techniques for linear features detection in multitemporal sar images, IEEE Transactions on Geoscience and Remote sensing, vol.37, pp.1292-1305, 1999.
URL : https://hal.archives-ouvertes.fr/hal-00799807

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.

N. Cho, A. Yuille, and S. Lee, A novel linelet-based representation for line segment detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.40, pp.1195-1208, 2018.

M. Dai, C. Peng, A. 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.

C. Deledalle, L. Denis, S. Tabti, and F. Tupin, MuLoG, or how to apply gaussian denoisers to multi-channel sar speckle reduction ?, IEEE Transactions on Image Processing, vol.26, pp.4389-4403, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01388858

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

A. Desolneux, L. Moisan, and J. Morel, Meaningful alignments, International Journal of Computer Vision, vol.40, pp.7-23, 2000.

A. Desolneux, L. Moisan, and J. Morel, From Gestalt Theory to Image Analysis. A Probabilistic Approach, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00259077

P. Dollar and C. L. Zitnick, Fast edge detection using structured forests, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, pp.1558-1570, 2015.

K. W. Dougherty, C. Bozyer, and . Kranenburg, Roc curves evaluation of edge detector performance, Proceedings 1998 International Conference on Image Processing, vol.2, pp.525-529, 1998.

R. O. Duda and P. E. Hart, Use of the hough transformation to detect lines and curves in pictures, Communications of the ACM, vol.15, pp.11-15, 1972.

R. Fjørtoft, A. Lopes, 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.

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

R. Grompone-von-gioi, J. Jakubowicz, J. Morel, and G. Randall, Lsd : A fast line segment detector with a false detection control, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.32, pp.722-732, 2010.

R. Grompone-von-gioi, J. Jakubowicz, J. Morel, and G. Randall, Lsd : a line segment detector, Image Processing On Line, vol.2, pp.35-55, 2012.

B. Grosjean and L. Moisan, A-contrario detectability of spots in textured backgrounds, Journal of Mathematical Imaging and Vision, vol.33, issue.3, pp.313-337, 2009.
URL : https://hal.archives-ouvertes.fr/hal-00534713

O. Hellwich and H. Mayer, Extracting line features from synthetic aperture radar (sar) scenes using a markov random field model, Proceedings of 3rd IEEE International Conference on Image Processing, vol.3, pp.883-886, 1996.

K. Huang, Y. Wang, Z. Zhou, T. Ding, S. Gao et al., Learning to parse wireframes in images of man-made environments, The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

J. Illingworth and J. Kittler, The adaptive hough transform, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.9, pp.690-698, 1987.

W. Jiang, K. Lam, and T. Zhi-shen, Efficient edge detection using simplified gabor wavelets, IEEE Transactions on Systems, Man, and Cybernetics, vol.39, pp.1036-1047, 2009.

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.

P. Kovesi, Symmetry and asymmetry from local phase, Tenth Australian joint conference on artificial intelligence, vol.190, pp.2-4, 1997.

A. Krizhevsky, I. Sutskever, and G. E. Hinton, Imagenet classification with deep convolutional neural networks, Neural Information Processing Systems (NIPS) 2012, pp.1106-1114, 2012.

A. Lapini, T. Bianchi, F. Argenti, and L. Alparone, Blind speckle decorrelation for SAR image despeckling, IEEE Transactions on Geoscience and Remote Sensing, vol.52, issue.2, 2014.

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

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.

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, p.2020
URL : https://hal.archives-ouvertes.fr/hal-01827482

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. 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.

D. R. Martin, C. C. Fowlkes, and J. 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.

F. Medeiros, R. Costa, R. Marques, and C. Laprano, Multiscale detection of linear features in speckled imagery, 16th Brazilian Symposium on Computer Graphics and Image Processing, pp.371-375, 2003.

A. Myaskouvskey, Y. Gousseau, and M. Lindenbaum, Beyond independence : An extension of the a contrario decision, International journal of Computer Vision, vol.101, pp.22-44, 2013.

F. O'gorman and M. Clowes, Finding picture edges through collinearity of feature points, IEEE Transactions on Computers, C, vol.25, pp.449-456, 1976.

C. Palmann, S. Mavromatis, and J. Sequeira, Sar image registration using a new approach based on the generalized hough transform, vol.XXXVII, 2008.
URL : https://hal.archives-ouvertes.fr/hal-01287595

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.

D. Shen, J. Zhang, J. Yang, D. Feng, and J. Li, Sar and optical image registration based on edge features, 4th International Conference on Systems and Informatics, 2017.

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.

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.37272-37285, 2018.

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.

K. Simonyan and A. Zisserman, Very deep convolutional networks for large-scale image recognition, International Conference on Learning Representations, 2015.

J. Skingley and A. Rye, The hough transform applied to sar images for thin line detection, Pattern Recognition Letters, vol.6, pp.61-67, 1987.

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.

H. Sui, C. Xu, J. Liu, and F. Hua, Automatic optical-to-sar image registration by iterative line extraction and voronoi integrated spectral point matching, IEEE Transactions on Geoscience and Remote Sensing, vol.53, pp.6058-6072, 2015.

R. Touzi, A. Lopes, 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.

F. Tupin, H. Maître, J. Mangin, J. Nicolas, and E. Pechersky, Detection of linear features in sar images : application to road network, IEEE Transactions on Geoscience and Remote Sensing, vol.36, pp.434-453, 1998.

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.

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.

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

S. Xie and Z. Tu, Holistically-nested edge detection, International Journal of Computer Vision, vol.125, pp.3-18, 2017.

B. Xiong, W. Li, L. Zhao, J. Lu, X. Zhang et al., Registration for sar and optical images based on straight line features and mutual information, 2016 IEEE International Geoscience and and Remote Sensing Symposium, 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, Conferece on Neural Information Processing Systems, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01646112

F. Xu and Y. Jin, Automatic reconstruction of building objects from multiaspect meterresolution sar images, IEEE Transactions on Geoscience and Remote Sensing, vol.45, pp.2336-2353, 2007.

N. Xue, S. Bai, F. Wang, G. Xia, T. Wu et al., Learning attraction field representation for robust line segment detection, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.1595-1603, 2019.

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.

P. Yu, A. 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.

G. Zhang, H. Sui, Z. Song, F. Hua, and L. Hua, Automatic registration method of sar and optical image based on line features and spectral graph theory, 2017 2nd International Conference on Multimedia and Image Processing, 2017.

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. Zhao, Y. Wu, S. Pan, F. Zhou, B. An et al., Automatic registration of images with inconsistent content through line support region segmentation and geometrical outlier removal, IEEE Transactions on Image Processing, vol.27, pp.2731-2746, 2018.