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Review Article

SAR image edge detection: review and benchmark experiments

& ORCID Icon
Pages 5372-5438 | Received 23 Mar 2022, Accepted 26 Sep 2022, Published online: 25 Oct 2022

References

  • Achim, A., P. Tsakalides, and A. Bezerianos. 2003. “SAR Image Denoising via Bayesian Wavelet Shrinkage Based on Heavy-Tailed Modeling.” IEEE Transactions on Geoscience and Remote Sensing 41 (8): 1773–1784. doi:10.1109/TGRS.2003.813488.
  • Ahmadi, H., and E. Pekkan. 2021. “Fault-Based Geological Lineaments Extraction Using Remote Sensing and GIS— A Review.” Geosciences 11 (5): 183. doi:10.3390/geosciences11050183.
  • Arbelaez, P., M. Maire, C. Fowlkes, and J. Malik. 2011. “Contour Detection and Hierarchical Image Segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence 33 (5): 898–916. doi:10.1109/TPAMI.2010.161.
  • Bachofer, F., G. Queneherve, T. Zwiener, M. Marker, and V. Hochschild. 2016. “Comparative Analysis of Edge Detection Techniques for SAR Images.” European Journal of Remote Sensing 49 (1): 205–224.
  • Bakula, K., J. P. Mills, and F. Remondino. 2019. ”A Review of Benchmarking in Photogrammetry and Remote Sensing.” International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W2: XLII-1/W2. doi:10.5194/isprs-archives-XLII-1-W2-1-2019.
  • Bogdan, V., C. Bonchis, and C. Orhei. 2020. “Custom Dilated Edge Detection Filters.” In International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision. Plzen, Czech Republic.
  • Boncelet, C. 2009. ”Chapter 7 - Image Noise Models.” In The Essential Guide to Image Processing, edited by A. Bovik, 143–167. Boston: Academic Press.
  • Bradski, G. 2000. “The OpenCV Library.” Dr Dobb’s Journal of Software Tools 120: 122–125.
  • Buades, A., B. Coll, and J. M. Morel. 2005. “A Non-Local Algorithm for Image Denoising.“ IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA.
  • Byun, J., S. Cha, and T. Moon. 2021. “FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noise.” In IEEE Conference on Computer Vision and Pattern Recognition, Nashville, TN, USA.
  • Canny, J. 1986. “A Computational Approach to Edge Detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence 8 (6): 679–698.
  • Chen, L., Q. Zhu, X. Xie, H. Hu, and H. Zeng. 2018. “Road Extraction from VHR Remote-Sensing Imagery via Object Segmentation Constrained by Gabor Features.” ISPRS International Journal of Geo-Information 7 (9): 1–21.
  • Cordts, M., M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele. 2016. “The Cityscapes Dataset for Semantic Urban Scene Understanding.” In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA, 3213–3223.
  • Cozzolino, D., L. Verdoliva, G. Scarpa, and G. Poggi. 2020. “Nonlocal CNN SAR Image Despeckling.” Remote Sensing 12 (6): 1006. doi:10.3390/rs12061006.
  • Dabov, K., A. Foi, V. Katkovnik, and K. Egiazarian. 2007. “Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering.” IEEE Transactions on Image Processing 16 (8): 2080–2095. doi:10.1109/TIP.2007.901238.
  • Dalsasso, E., L. Denis, and F. Tupin. 2021. “SAR2SAR: A Semi-Supervised Despeckling Algorithm for SAR Images.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14: 4321–4329. doi:10.1109/JSTARS.2021.3071864.
  • Daugman, J. G. 1985. “Uncertainty Relation for Resolution in Space, Spatial Frequency, and Orientation Optimized by Two-Dimensional Visual Cortical Filters.” Journal of the Optical Society of America A 2 (7): 1160–1169. doi:10.1364/JOSAA.2.001160.
  • Dellinger, F., J. Delon, Y. Gousseau, J. Michel, and F. Tupin. 2015. “SAR-SIFT: A SIFT-Like Algorithm for SAR Images.” IEEE Transactions on Geoscience and Remote Sensing 53 (1): 453–466. doi:10.1109/TGRS.2014.2323552.
  • D’Hondt, O., S. Guillaso, and O. Hellwich. 2013. “Iterative Bilateral Filtering of Polarimetric SAR Data.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6 (3): 1628–1639. doi:10.1109/JSTARS.2013.2256881.
  • Doersch, C., A. Gupta, and A. A. Efros. 2015. “Unsupervised Visual Representation Learning by Context Prediction.” In IEEE International Conference on Computer Vision, Santiago, Chile.
  • Duda, R., and P. Hart. 1973. Pattern Classification and Scene Analysis. New York: John Wiley & Sons.
  • Everingham, M., S. M. A. Eslami, L. van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. 2015. “The Pascal Visual Object Classes Challenge: A Retrospective.” International Journal of Computer Vision 111 (1): 98–136.
  • Farbod, M., G. Akbarizadeh, A. Kosarian, and K. Rangzan. 2018. “Optimized Fuzzy Cellular Automata for Synthetic Aperture Radar Image Edge Detection.” Journal of Electronic Imaging 27 (1): 013030. doi:10.1117/1.JEI.27.1.013030.
  • Farid, H., and E. P. Simoncelli. 2004. “Differentiation of Discrete Multidimensional Signals.” IEEE Transactions on Image Processing 13 (4): 496–508. doi:10.1109/TIP.2004.823819.
  • Fawwaz, I., M. Zarlis, and R. F. Rahmat. 2018. “The Edge Detection Enhancement on Satellite Image Using Bilateral Filter.” IOP Conference Series: Materials Science and Engineering: Iop Conference Series: Materials Science and Engineering 308: 012052. doi:10.1088/1757-899X/308/1/012052.
  • Fracastoro, G., E. Magli, G. Poggi, G. Scarpa, D. Valsesia, and L. Verdoliva. 2021. “Deep Learning Methods for Synthetic Aperture Radar Image Despeckling: An Overview of Trends and Perspectives.“ IEEE Geoscience and Remote Sensing Magazine 9 (2): 29- 51 .
  • Frei, W., and C. C. Chen. 1977. “Fast Boundary Detection: A Generalization and a New Algorithm.” IEEE Transactions on Computers 26 (10): 988–998.
  • Goodman, J. W. 1975. Statistical Properties of Laser Speckle Patterns, 9–75. Berlin, Heidelberg: Springer.
  • Gou, S., D. Li, D. Hai, W. Chen, F. Du, and L. Jiao. 2018. “Spectral Clustering with Eigenvalue Similarity Metric Method for POL-SAR Image Segmentation of Land Cover.” Journal of Geographic Information System 10 (1): 150–164. doi:10.4236/jgis.2018.101007.
  • Grizonnet, M., J. Michel, V. Poughon, J. Inglada, M. Savinaud, and R. Cresson. 2017. “Orfeo Toolbox: Open Source Processing of Remote Sensing Images.” Open Geospatial Data, Software and Standards 2 (1). doi:10.1186/s40965-017-0031-6.
  • Gupta, R., B. Goodman, N. Patel, R. Hosfelt, S. Sajeev, E. Heim, J. Doshi, K. Lucas, H. Choset, and M. Gaston. 2019. “Creating xBD: A Dataset for Assessing Building Damage from Satellite Imagery.” In IEEE Conference on Computer Vision and Pattern Recognition Workshops, Long Beach, CA, USA.
  • Gupta, A., A. Tripathi, and V. Bhateja. 2013. “Despeckling of SAR Images via an Improved Anisotropic Diffusion Algorithm.” In International Conference on Frontiers of Intelligent Computing: Theory and Applications, Bhubaneswar, Odisha, India.
  • He, K., J. Sun, and X. Tang. 2013. “Guided Image Filtering.” IEEE Transactions on Pattern Analysis and Machine Intelligence 35 (6): 1397–1409. doi:10.1109/TPAMI.2012.213.
  • He, K., X. Zhang, S. Ren, and J. Sun. 2016. “Deep Residual Learning for Image Recognition.” In IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA.
  • He, J., S. Zhang, M. Yang, Y. Shan, and T. Huang. 2020. “BDCN: Bi-Directional Cascade Network for Perceptual Edge Detection.“ IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (1): 100–113.
  • Hua, Y., D. Marcos, L. Mou, X. X. Zhu, and D. Tuia. 2022. “Semantic Segmentation of Remote Sensing Images with Sparse Annotations.” IEEE Geoscience and Remote Sensing Letters 19: 1–5. doi:10.1109/LGRS.2021.3051053.
  • Huang, L., B. Liu, B. Li, W. Guo, W. Yu, Z. Zhang, and W. Yu. 2018. “OpenSARShip: A Dataset Dedicated to Sentinel-1 Ship Interpretation.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11 (1): 195–208. doi:10.1109/JSTARS.2017.2755672.
  • Huang, G., Z. Liu, L. van der Maaten, and K. Q. Weinberger. 2017. “Densely Connected Convolutional Networks.” In IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.
  • Huang, M., Y. Xu, L. Qian, W. Shi, Y. Zhang, W. Bao, N. Wang, X. Liu, and X. Xiang. 2021. ”The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusion.” arXiv preprint arXiv:2103.08259v2.
  • Hu, J., L. Shen, and G. Sun. 2018. “Squeeze-And-Excitation Networks.” In IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.
  • Jain, P., and V. Tyagi. 2016. “A Survey of Edge-Preserving Image Denoising Methods.” Information Systems Frontiers 18 (1): 159–170. doi:10.1007/s10796-014-9527-0.
  • Jaritz, M., R. D. Charette, E. Wirbel, X. Perrotton, and F. Nashashibi. 2018. “Sparse and Dense Data with CNNs: Depth Completion and Semantic Segmentation.” In International Conference on 3D Vision (3DV), Verona, Italy.
  • Junior, G. P. S., A. C. Frery, S. Sandri, H. Bustince, E. Barrenechea, and C. Marco-Detchart. 2015. “Optical Images-Based Edge Detection in Synthetic Aperture Radar Images.” Knowledge-Based Systems 87: 38–46.
  • Kekre, H. B., and S. M. Gharge. 2010. “Image Segmentation Using Extended Edge Operator for Mammographic Images.” International Journal on Computer Science and Engineering 2 (4): 1086–1091.
  • Khan, S., A. Khan, M. Maqsood, F. Aadil, and M. A. Ghazanfar. 2019. “Optimized Gabor Feature Extraction for Mass Classification Using Cuckoo Search for Big Data E-Healthcare.” Journal of Grid Computing 17 (2): 239–254. doi:10.1007/s10723-018-9459-x.
  • Kim, D. W., J. R. Chung, and S. W. Jung. 2019. “GRDN:Grouped Residual Dense Network for Real Image Denoising and GAN-based Real-World Noise Modeling.” In IEEE Conference on Computer Vision and Pattern Recognition Workshops, Long Beach, CA, USA.
  • Krizhevsky, A. 2009. “Learning Multiple Layers of Features from Tiny Images.” Technical report, University of Toronto.
  • Krizhevsky, A., I. Sutskever, and G. E. Hinton. 2012. “ImageNet Classification with Deep Convolutional Neural Networks.“ In Advances in Neural Information Processing Systems, Nevada, GA, USA.
  • Labate, D., W. Q. Lim, G. Kutyniok, and G. Weiss. 2005. “Sparse Multidimensional Representation Using Shearlets.” In Proceedings of SPIE 5914, Wavelets XI, 59140U, San Diego, CA, USA.
  • Larsson, G., M. Maire, and G. Shakhnarovich. 2017. “Colorization as a Proxy Task for Visual Understanding.” In IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.
  • Lateef, R. A. R. 2008. “Expansion and Implementation of a 3x3 Sobel and Prewitt Edge Detection Filter to a 5x5 Dimension Filter.” Journal of Baghdad College of Economic Sciences University 1 (18): 336–348.
  • Lattari, F., B. G. Leon, F. Asaro, A. Rucci, C. Prati, and M. Matteucci. 2019. “Deep Learning for SAR Image Despeckling.” Remote Sensing 11 (13): 1532. doi:10.3390/rs11131532.
  • LeCun, Y., L. Bottou, Y. Bengio, and P. Haffner. 1998. “Gradient-Based Learning Applied to Document Recognition.” Proceedings of the IEEE 86 (11): 2278–2324. doi:10.1109/5.726791.
  • Lee, G. R., R. Gommers, F. Waselewski, K. Wohlfahrt, and A. O’Leary. 2019. “PyWavelets: A Python Package for Wavelet Analysis.” Journal of Open Source Software 4 (36): 1237. doi:10.21105/joss.01237.
  • Lin, T. Y., M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollar, and C. L. Zitnick. 2014. “Microsoft COCO: Common Objects in Context.” In European Conference on Computer Vision, Zurich, Switzerland: Springer. 740–755.
  • Liu, Y., M. M. Cheng, X. Hu, J. W. Bian, L. Zhang, X. Bai, and J. Tang. 2019. “Richer Convolutional Features for Edge Detection.” IEEE Transactions on Pattern Analysis and Machine Intelligence 41 (8): 1939–1946.
  • Liu, C., F. Tupin, and Y. Gousseau. 2020. “Training CNNs on Speckled Optical Dataset for Edge Detection in SAR Images.” ISPRS Journal of Photogrammetry and Remote Sensing 170: 88–102. doi:10.1016/j.isprsjprs.2020.09.018.
  • Li, K., G. Wan, G. Cheng, L. Meng, and J. Han. 2020. “Object Detection in Optical Remote Sensing Images: A Survey and a New Benchmark.” ISPRS Journal of Photogrammetry and Remote Sensing 159: 296–307. doi:10.1016/j.isprsjprs.2019.11.023.
  • Li, J., W. Yu, Z. Wang, Y. Luo, and Z. Yu. 2022. “A Robust Statistic-Aided Edge Detector for SAR Images Based on RUSTICO.” Electronics Letters 58 (10): 393–395. doi:10.1049/ell2.12473.
  • Luo, Y., D. An, W. Wang, and X. Huang. 2020. “Improved ROEWA SAR Image Edge Detector Based on Curvilinear Structures Extraction.” IEEE Geoscience and Remote Sensing Letters 17 (4): 631–635. doi:10.1109/LGRS.2019.2926428.
  • Makinen, Y., L. Azzari, and A. Foi. 2020. “Collaborative Filtering of Correlated Noise: Exact Transform-Domain Variance for Improved Shrinkage and Patch Matching.” IEEE Transactions on Image Processing 29: 8339–8354. doi:10.1109/TIP.2020.3014721.
  • Maksimovic, V., P. Lekic, M. Petrovic, B. Jaksic, and P. Spalevic. 2019. “Experimental Analysis of Wavelet Decomposition on Edge Detection.” Proceedings of the Estonian Academy of Sciences 68 (3): 284–298. doi:10.3176/proc.2019.3.06.
  • Marmanis, D., M. Datcu, T. Esch, and U. Stilla. 2015. “Deep Learning Earth Observation Classification Using ImageNet Pretrained Networks.” IEEE Geoscience and Remote Sensing Letters 13 (1): 105–109.
  • Marr, D., and E. Hildreth. 1980. “Theory of Edge Detection.” Proceedings of the Royal Society of London Series B Biological Sciences 207 (1167): 187–217.
  • Min, W., and Y. Shuyuan. 2005. “A Hybrid Genetic Algorithm-Based Edge Detection Method for SAR Image.” In IEEE International Radar Conference, Arlington, VA, USA.
  • Molini, A. B., D. Valsesia, G. Fracastoro, and E. Magli. 2020. “Towards Deep Unsupervised SAR Despeckling with Blind-Spot Convolutional Neural Networks.” In IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, 2507–2510. IEEE.
  • Molini, A. B., D. Valsesia, G. Fracastoro, and E. Magli. 2021. “Speckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks.“ IEEE Transactions on Geoscience and Remote Sensing 60 (1): 5204017.
  • Naumenko, A., V. Lukin, and K. Egiazarian. 2012. “SAR-Image Edge Detection Using Artificial Neural Network.” In International Conference on Mathematical Methods in Electromagnetic Theory, Kharkiv, Ukraine.
  • Nava, R., B. Escalante-Ramirez, and G. Cristobal. 2011. “A Comparison Study of Gabor and Log-Gabor Wavelets for Texture Segmentation.” In International Symposium on Image and Signal Processing and Analysis, Dubrovnik, Croatia.
  • Ouchi, K. 1985. “On the Multilook Images of Moving Targets by Synthetic Aperture Radars.” IEEE Transactions on Antennas and Propagation 33 (8): 823–827. doi:10.1109/TAP.1985.1143684.
  • Parrilli, S., M. Poderico, C. V. Angelino, and L. Verdoliva. 2011. “A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage.” IEEE Transactions on Geoscience and Remote Sensing 50 (2): 606–616.
  • Parrilli, S., M. Poderico, C. V. Angelino, and L. Verdoliva. 2012. “A Nonlocal SAR Image Denoising Algorithm Based on LLMMSE Wavelet Shrinkage.” IEEE Transactions on Geoscience and Remote Sensing 50 (2): 606–616. doi:10.1109/TGRS.2011.2161586.
  • Perona, P., and J. Malik. 1990. “Scale-Space and Edge Detection Using Anisotropic Diffusion.” IEEE Transactions on Pattern Analysis and Machine Intelligence 12 (7): 629–639. doi:10.1109/34.56205.
  • Pour, A. B., T. Y. S. Park, Y. Park, J. K. Hong, A. M. Muslim, A. Laufer, L. Crispini, et al. 2019. “Landsat-8, Advanced Spaceborne Thermal Emission and Reflection Radiometer, and Worldview-3 Multispectral Satellite Imagery for Prospecting Copper-Gold Mineralization in the Northeastern Inglefield Mobile Belt (IMB), Northwest Greenland.” Remote Sensing 11 (20): 2430.
  • Prewitt, J. M. S. 1970. “Object Enhancement and Extraction.” Picture Processing and Psychopictorics 10 (1): 15–19.
  • Rahnemoonfar, M., T. Chowdhury, A. Sarkar, D. Varshney, M. Yari, and R. R. Murphy. 2021. “FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding.” IEEE Access 9: 89644–89654. doi:10.1109/ACCESS.2021.3090981.
  • Reisenhofer, R., J. Kiefer, and E. J. King. 2016. “Shearlet-based Detection of Flame Fronts.” Experiments in Fluids 57: 41.
  • Renshaw, D. T., and J. A. Christian. 2020. “Subpixel Localization of Isolated Edges and Streaks in Digital Images.” Journal of Imaging 6 (5): 33. doi:10.3390/jimaging6050033.
  • Roberts, L. G. 1963. “Machine Perception of Three-Dimensional Solids.” PhD thesis, Massachusetts Institute of Technology.
  • Russakovsky, O., J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, et al. 2015. “ImageNet Large Scale Visual Recognition Challenge.” International Journal of Computer Vision 115 (3): 211–252. doi:10.1007/s11263-015-0816-y.
  • Salberg, A. 2015. “Detection of Seals in Remote Sensing Images Using Features Extracted from Deep Convolutional Neural Networks.” In 2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Milan, Italy: IEEE. 1893–1896.
  • Scharr, H. 2000. “Optimal Operators in Digital Image Processing.” PhD thesis, Rupertus Carola University of Heidelberg.
  • Schou, J., H. Skriver, A. A. Nielsen, and K. Conradsen. 2003. “CFAR Edge Detector for Polarimetric SAR Images.” IEEE Transactions on Geoscience and Remote Sensing 41 (1): 20–32. doi:10.1109/TGRS.2002.808063.
  • Schowengerdt, R. A. 2007. ”Chapter 6 - Spatial Transforms”. In Remote Sensing (Third Edition), 3rd ed. edited by R. A. Schowengerdt, 229–283. Burlington: Academic Press.
  • Shang, R., P. Peng, F. Shang, L. Jiao, Y. Shen, and R. Stolkin. 2020. “Semantic Segmentation for SAR Image Based on Texture Complexity Analysis and Key Superpixels.” Remote Sensing 12 (13): 2141. doi:10.3390/rs12132141.
  • Sharma, R. K., B. S. Kumar, N. M. Desai, and V. R. Gujraty. 2008. “SAR for Disaster Management.” IEEE Aerospace and Electronic Systems Magazine 23 (6): 4–9. doi:10.1109/MAES.2008.4558001.
  • Shermeyer, J., D. Hogan, J. Brown, A. van Etten, N. Weir, F. Pacifici, R. Hansch, et al. 2020. “SpaceNet 6: Multi-Sensor All Weather Mapping Dataset.” In IEEE Conference on Computer Vision and Pattern Recognition Workshops, Seattle, WA, USA.
  • Shui, P. L., and D. Cheng. 2012. “Edge Detector of SAR Images Using Gaussian-Gamma-Shaped Bi-Windows.” IEEE Geoscience and Remote Sensing Letters 9 (5): 846–850.
  • Sica, F., D. Cozzolino, X. X. Zhu, L. Verdoliva, and G. Poggi. 2018. “InSAR-BM3D: A Nonlocal Filter for SAR Interferometric Phase Restoration.” IEEE Transactions on Geoscience and Remote Sensing 56 (6): 3456–3467. doi:10.1109/TGRS.2018.2800087.
  • Simonyan, K., and A. Zisserman. 2015. “Very Deep Convolutional Networks for Large-Scale Image Recognition.” In International Conference on Learning Representations, San Diego, CA, USA.
  • Singh, P., and R. Shree. 2016. “Analysis and Effects of Speckle Noise in SAR Images.” In International Conference on Advances in Computing, Communication & Automation (ICACCA)(Fall), Bareilly, India.
  • Soldal, I. H., W. Dierking, A. Korosov, and A. Marino. 2019. “Automatic Detection of Small Icebergs in Fast Ice Using Satellite Wide-Swath SAR Images.” Remote Sensing 11 (7): 1–24. doi:10.3390/rs11070806.
  • Sponton, H., and J. Cardelino. 2015. “A Review of Classic Edge Detectors.” Image Processing on Line 5: 90–123. doi:10.5201/ipol.2015.35.
  • Stojnic, V., and V. Risojevic. 2021. “Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Coding.” In IEEE Conference on Computer Vision and Pattern Recognition Workshops, Nashville, TN, USA.
  • Strisciuglio, N., G. Azzopardi, and N. Petkov. 2019a. “Robust Inhibition-Augmented Operator for Delineation of Curvilinear Structures.” IEEE Transactions on Image Processing, 1.
  • Strisciuglio, N., G. Azzopardi, and N. Petkov. 2019b. “Robust Inhibition-Augmented Operator for Delineation of Curvilinear Structures.” IEEE Transactions on Image Processing 28 (12): 5852–5866. doi:10.1109/TIP.2019.2922096.
  • Sun, Z., G. Zhao, W. Chen, R. Damasevicius, and M. Wozniak. 2022. “Edge Detection of SAR Images Based on Shearlet.” In China High Resolution Earth Observation Conference, Changsha, China.
  • Sun, Z., G. Zhao, M. Wozniak, R. Scherer, and R. Damasevicius. 2021. “Bankline Detection of GF-3 SAR Images Based on Shearlet.” PeerJ Computer Science 7: e611. doi:10.7717/peerj-cs.611.
  • Szegedy, C., W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich. 2015. “Going Deeper with Convolutions.” In IEEE Conference on Computer Vision and Pattern Recognition, Boston, MA, USA.
  • Tadic, V., T. Loncar-Turukalo, A. Odry, Z. Trpovski, A. Toth, Z. Vizvari, and P. Odry. 2021. “A Note on Advantages of the Fuzzy Gabor Filter in Object and Text Detection.” Symmetry 13 (4): 678. doi:10.3390/sym13040678.
  • Tan, M., and Q. V. Le. 2019. “EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.” In International Conference on Machine Learning, Long Beach, CA, USA.
  • Tao, C., J. Qi, W. Lu, H. Wang, and H. Li. 2020. “Remote Sensing Image Scene Classification with Self-Supervised Paradigm Under Limited Labeled Samples.” IEEE Geoscience and Remote Sensing Letters 19: 8004005.
  • Tian, C., Y. Xu, Z. Li, W. Zuo, L. Fei, and H. Liu. 2020. “Attention-Guided CNN for Image Denoising.” Neural Networks 124 (1): 117–129. doi:10.1016/j.neunet.2019.12.024.
  • Tomasi, C., and R. Manduchi. 1998. “Bilateral Filtering for Gray and Color Images.” In IEEE International Conference on Computer Vision, Bombay, India.
  • Touzi, R., A. Lopes, and P. Bousquet. 1988. “A Statistical and Geometrical Edge Detector for SAR Images.” IEEE Transactions on Geoscience and Remote Sensing 26 (6): 764–773. doi:10.1109/36.7708.
  • Trujillo-Pino, A., K. Krissian, M. Aleman-Flores, and D. Santana-Cedres. 2013. “Accurate Subpixel Edge Location Based on Partial Area Effect.” Image and Vision Computing 31 (1): 72–90. doi:10.1016/j.imavis.2012.10.005.
  • van der Walt, S., J. L. Schonberger, J. N. Iglesias, F. Boulogne, J. D. Warner, N. Yager, E. Gouillart, T. Yu, and the scikit-image contributors. 2014. ”Scikit-Image: Image Processing in Python.” PeerJ 2: e453.
  • van Etten, A., D. Lindenbaum, and T. Bacastow. 2019. “SpaceNet: A Remote Sensing Dataset and Challenge Series.” arXiv preprint arXiv:1807.01232v3.
  • Vitale, S., G. Ferraioli, and V. Pascazio. 2021. “Multi-Objective CNN-Based Algorithm for SAR Despeckling.“ IEEE Transactions on Geoscience and Remote Sensing 59 (11): 9336- 9349.
  • Wang, M., L. Gao, X. Huang, Y. Jiang, and X. Gao. 2019. “A Texture Classification Approach Based on the Integrated Optimization for Parameters and Features of Gabor Filter via Hybrid Ant Lion Optimizer.” Applied Sciences 9 (11): 2173. doi:10.3390/app9112173.
  • Wei, Q. R., and D. Z. Feng. 2015. “An Efficient SAR Edge Detector with a Lower False Positive Rate.” International Journal of Remote Sensing 36 (14): 3773–3797.
  • Wei, Q. R., and D. Z. Feng. 2018. “Antistretch Edge Detector for SAR Images.” IEEE Geoscience and Remote Sensing Letters 15 (9): 1382–1386.
  • Wei, S., X. Zeng, Q. Qu, M. Wang, H. Su, and J. Shi. 2020. “HRSID: A High-Resolution SAR Images Dataset for Ship Detection and Instance Segmentation.” IEEE Access 8: 120234–120254. doi:10.1109/ACCESS.2020.3005861.
  • Xia, G. S., X. Bai, J. Ding, Z. Zhu, S. Belongie, J. Luo, M. Datcu, M. Pelillo, and L. Zhang. 2018. “DOTA: A Large-Scale Dataset for Object Detection in Aerial Images.” In IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA.
  • Xiang, Y., F. Wang, L. Wan, and H. You. 2017a. “An Advanced Multiscale Edge Detector Based on Gabor Filters for SAR Imagery.” IEEE Geoscience and Remote Sensing Letters 14 (9): 1522–1526. doi:10.1109/LGRS.2017.2720684.
  • Xiang, Y., F. Wang, L. Wan, and H. You. 2017b. “SAR-PC: Edge Detection in Sar Images via an Advanced Phase Congruency Model.” Remote Sensing 9 (3): 209. doi:10.3390/rs9030209.
  • Xiao, J., K. A. Ehinger, J. Hays, A. Torralba, and A. Oliva. 2016. “Sun Database: Exploring a Large Collection of Scene Categories.” International Journal of Computer Vision 119 (1): 3–22. doi:10.1007/s11263-014-0748-y.
  • Xie, S., and Z. Tu. 2015. “Holistically-Nested Edge Detection.” In IEEE International Conference on Computer Vision, Santiago, Chile.
  • Yang, Y., and S. Newsam. 2010. “Bag-Of-Visual-Words and Spatial Extensions for Land-Use Classification.” In ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, San Jose, CA, USA.
  • Yi, S., D. Labate, G. R. Easley, and H. Krim. 2009. “A Shearlet Approach to Edge Analysis and Detection.” IEEE Transactions on Image Processing 18 (5): 929–941. doi:10.1109/TIP.2009.2013082.
  • Zhang, Z., Y. Liu, T. Liu, Y. Li, and W. Ye. 2019. “Edge Detection Algorithm of a Symmetric Difference Kernel SAR Image Based on the GAN Network Model.” Symmetry 11 (4): 557.
  • Zhang, K., W. Zuo, Y. Chen, D. Meng, and L. Zhang. 2017. “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising.” IEEE Transactions on Image Processing 26 (7): 3142–3155. doi:10.1109/TIP.2017.2662206.
  • Zhang, K., W. Zuo, and L. Zhang. 2018. “FFDNet: Toward a Fast and Flexible Solution for CNN-based Image Denoising.” IEEE Transactions on Image Processing 27 (9): 4608–4622. doi:10.1109/TIP.2018.2839891.
  • Zhan, Y., H. You, and C. Fuqing. 2013. “Bayesian Edge Detector for SAR Imagery Using Discontinuity-Adaptive Markov Random Field Modeling.” Chinese Journal of Aeronautics 26 (6): 1534–1543. doi:10.1016/j.cja.2013.04.059.
  • Zhao, H., Q. Wang, W. Wu, Q. Wang, and N. Yuan. 2014. “SAR Image Despeckling Based on Improved Non-Local Means Algorithm.” In International Conference on Electromagnetics in Advanced Applications, Palm Beach, Aruba.
  • Zhao, J., Z. Zhang, W. Yao, M. Datcu, H. Xiong, and W. Yu. 2020. “OpenSARUrban: A Sentinel-1 SAR Image Dataset for Urban Interpretation.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13: 187–203. doi:10.1109/JSTARS.2019.2954850.
  • Zhou, W., S. Newsam, C. Li, and Z. Shao. 2018. “PatternNet: A Benchmark Dataset for Performance Evaluation of Remote Sensing Image Retrieval.” ISPRS Journal of Photogrammetry and Remote Sensing 145: 197–209. doi:10.1016/j.isprsjprs.2018.01.004.
  • Zhu, X. X., J. Hu, C. Qiu, Y. Shi, J. Kang, L. Mou, H. Bagheri, et al. 2020. “So2Sat LCZ42: A Benchmark Data Set for the Classification of Global Local Climate Zones.” IEEE Geoscience and Remote Sensing Magazine 8 (3): 76–89.