Abstract
Synthetic aperture radar (SAR) has the characteristics of all-weather imaging and is widely used in various fields. However, owe to coherent imaging mechanism, speckle appears in SAR images, which seriously affects the interpretation of images. Due to merits of the strong directional sensitivity and the optimal sparsity, shearlet is used to construct an edge detector for SAR images. The detector firstly converts the constructed even symmetric shearlet into odd symmetry by Hilbert transform, then determines the main direction of the edge according to the odd symmetric shearlet coefficient of the SAR image, and calculates the possibility of edge existence according to both odd and even symmetric shearlet coefficient. Experiments show that, in comparison with the traditional difference-based edge detectors, the proposed edge detector has stronger ability of anti-speckle interference, and can better detect the edge information in SAR images.
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References
Shao W, Yuan X, Sheng Y, Sun J, Zhou W, Zhang Q (2018) Development of wind speed retrieval from cross-polarization chinese Gaofen-3 synthetic aperture radar in typhoons. Sensors 18:412–427
Wang J, Bi J, Wang L, Wang X (2018) A non-reference evaluation method for edge detection of wear particles in ferrograph images. Mech Syst Signal Process 100:863–876
Li J, Huang S, Peng Y, Zhang W (2012) A novel method to configure the parameters of the bilateral filtering for synthetic aperture radar images speckle reduction. ActaPhysicaSinica. 61:9501–9505
Reisenhofer R, Kiefer J, King EJ (2016) Shearlet-based detection of flame fronts. Exp Fluids 57:41–54
Yang D, Lu C, Zhang J, Yang K, Chen X (2013) Edge detection of SAR images based on ROEWA and Hough transform. J Electron Measur Instr 27:543–548
An Q, Pan Z, You H (2018) Ship detection in gaofen-3 SAR images based on sea clutter distribution analysis and deep convolutional neural network. Sensors 18:34–354
Shao W, Sheng Y, Sun J (2017) Preliminary assessment of wind and wave retrieval from chinese Gaofen-3 SAR imagery. Sensors 17:1705–1717
Kutyniok G, Labate D (2012) Shearlets: Multiscale analysis for multivariate data, Birkhäuser Basel, New York, USA, pp 30–31
Yuan Y, **e L, Zhu Y, Wang S, Zhuang Z (2017) SAR image de-noising using local properties analysis and discrete non-separable shearlet transform. In: 2017 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI) IEEE, Shanghai, China, October 14, 2017
Easley G, Labate D, Lim WQ (2008) Sparse directional image representation using the discrete shearlet transform. Appl Comput Harmon Anal 25:25–46
Liu S, Hu S, **ao Y (2013) SAR image de-noising based on complex shearlet transform domain Gaussian mixture model. Acta Aeronautica et Astronautica Sinica. 34:173–180
Lim WQ (2010) The discrete shearlet transform: a new directional transform and compactly supported shearlet frames. IEEE Trans Image Process 19:1166–1180
Huang Z, Ding M, Zhang X (2017) Medical image fusion based on non-subsampled shearlet transform and spiking cortical model. J Med Imaging Health Inf 7(2017):229–234
King EJ, Reisenhofer R, Kiefer J, Lim W-Q, Li Z, Heygster G (2015) Shearlet-based edge detection: flame fronts and tidal flats. Appl Digital Image Process XXXVIII:9599
Yan B, Yang J (2004) Analysis and research on Hilbert transform. J Electric Electron Educ 26:27–29
Zheng J (2014) Local feature scale decomposition method and its application in mechanical fault diagnosis. Hunan University, Changsha, China
Selesnick IW (2001) Hilbert transform pairs of wavelet bases. IEEE Signal Process Lett 8:170–173
Ding W, Wang W, Zhang X, Su L (2010) Extracting straight lines from building image based on edge orientation image. Acta Optica Sinica. 30:2904–2911
Wisaeng K, Sa-Ngiamvibool W (2018) Improved fuzzy C-means clustering in the process of exudates detection using mathematical morphology. Soft Comput 22:2753–2764
Bouaynaya N, Charif-Chefchaouni M, Schonfeld D (2007) Theoretical foundations of spatially-variant mathematical morphology part I: binary images. IEEE Trans Pattern Anal Mach Intell 30:823–836
Wang H, Zhan G (2009) Research and application of edge detection operator based on mathematical morphology. Comput Eng Appl 45:223–226
Huang X (2010) Locally univalent harmonic map**s with linearly connected image domains. Chin Ann Math 5:625–630
Étienne B, Frédéric N, Millon G, Ruan S (2008) Binary-image comparison with local-dissimilarity quantification. Pattern Recogn 41:1461–1478
Bouchara F, Ramdani S (2009) Subpixel edge refinement using deformable models. J Opt Soc Am A Optics Image Sci Vis 4:820–832
** L (2012) Separation and application of strong electromagnetic interference based on mathematical morphology. Central South University, Changsha, China
Reisenhofer R (2014) The complex shearlet transform and applications to image quality assessment. Technische Universität Berlin Fachgruppe Angewandte Funktionalanalysis, Berlin, Germany
Zhou B, Polap D, Wozniak M (2019) A regional adaptive variational PDE model for computed tomography image reconstruction. Pattern Recogn 92:64–81
**a X, Marcin W, Fan X, Damasevicius R, Li Y (2019) Multi-sink distributed power control algorithm for Cyber-physical-systems in coal mine tunnels. Comput Netw 161:210–219
Wei W, Houbing S, Wei L, Peiyi S, Athanasios V (2017) Gradient-driven parking navigation using a continuous information potential field based on wireless sensor network. Inf Sci 408:100–114
Wang X, Qi Y, Wang Z et al (2019) Design and implementation of SecPod: a framework for virtualization-based security systems. IEEE Trans Dependable Secure Comput 16:44–57
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Sun, Z., Zhao, G., Chen, W., Damaševičius, R., Woźniak, M. (2022). Edge Detection of SAR Images Based on Shearlet. In: Wang, L., Wu, Y., Gong, J. (eds) Proceedings of the 7th China High Resolution Earth Observation Conference (CHREOC 2020). CHREOC 2020. Lecture Notes in Electrical Engineering, vol 757. Springer, Singapore. https://doi.org/10.1007/978-981-16-5735-1_35
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