①(中国科学院电子学研究所 北京 100190) ②(中国科学院空间信息与应用系统重点实验室 北京 100190) ③(中国科学院大学 北京 100049) ④(Department of Physics and Technology, UiT The Arctic University of Norway, Tromso 9037)
Unsupervised Estimation of the Equivalent Number of Looks in PolSAR Image with High Heterogeneity
HU Dingsheng①②③ QIU Xiaolan①② Stian N. Anfinsen④ LEI Bin①②
①(Institute of Electronics, Chinese Academy of Science, Beijing 100190, China) ②(Key Laboratory of Technology in Geo-spatial Information Processing and Application System, Beijing 100190, China) ③(University of Chinese Academy of Science, Beijing 100049, China) ④(Department of Physics and Technology, UiT The Arctic University of Norway, Tromso 9037, Norway)
Abstract：Equivalent Number of Looks (ENL) is an important parameter in statistical modelling of multi-look Polarimetric SAR (PolSAR) data. In some automated applications of PolSAR images, it is necessary to estimate the ENL in an unsupervised way without any manual intervention. The existing unsupervised estimation of ENL can not obtain accurate estimates for the images with high heterogeneity. To address this issue, a novel unsupervised estimation method is proposed here. It combines the mixture elimination and clustering based on texture, which reduces the effect of two main heterogeneity factors, mixture and texture. The validity of this method is evaluated with simulated and real data of different complexity.
胡丁晟,仇晓兰,Stian N. Anfinsen,雷斌. 一种面向高异质性极化SAR图像的等效视数非监督估计方法[J]. 电子与信息学报, 2017, 39(10): 2287-2293.
HU Dingsheng, QIU Xiaolan, Stian N. Anfinsen, LEI Bin. Unsupervised Estimation of the Equivalent Number of Looks in PolSAR Image with High Heterogeneity. JEIT, 2017, 39(10): 2287-2293.
DOULGERIS A. An automatic U distribution and Markov random field segmentation algorithm for PolSAR images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2015, 53(4): 1819-1827. doi: 10.1109/TGRS.2014.2349575.
[2]
XU Qiao, CHEN Qihao, YANG Shuai, et al. Superpixel- based classification using K distribution and spatial context for polarimetric SAR images[J]. Remote Sensing, 2016, 8(8): 619. doi: 10.3390/rs8080619.
[3]
LIU Fang, SHI Junfei, JIAO Lichen, et al. Hierarchical semantic model and scattering mechanism based PolSAR image classification[J]. Pattern Recognition, 2016, 59: 325-342. doi: 10.1016/j.patcog.2016.02.020.
[4]
AKBARI V, ANFINSEN S, DOULGERIS A, et al. Polarimetric SAR change detection with the complex Hotelling & Lawley trace statistic[J]. IEEE Transactions on Geoscience and Remote Sensing, 2016, 54(7): 3953-3966. doi: 10.1109/TGRS.2016.2532320.
[5]
LIU Meng, ZHANG Hong, WANG Chao, et al. Polarimetric synthetic aperture radar change detection for specific land cover types[J]. International Journal of Digital Earth, 2016, 8(4): 334-344. doi: 10.1080/17538947.2013.872702.
[6]
ANFINSEN S, DOULGERIS A, and ELTOFT T. Estimation of the equivalent number of looks in polarimetric synthetic aperture radar imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(11): 3795-3809. doi: 10.1109/ TGRS.2009.2019269.
[7]
LIU Tao, CUI Haogui, XI Zemin, et al. Texture-invariant estimation of equivalent number of looks based on trace moments in polarimetric radar imagery[J]. IEEE Geoscience and Remote Sensing Letters, 2014, 11(6): 1129-1133. doi: 10.1109/LGRS.2013.2288097.
[8]
CUI Yi, ZHOU Guangyi, YANG Jian, et al. Unsupervised estimation of the equivalent number of looks in SAR images [J]. IEEE Geoscience and Remote Sensing Letters, 2011, 8(4): 710-714. doi: 10.1109/LGRS.2010.2102335.
[9]
LEE J and HOPPEL K. Noise modeling and estimation of remotely-sensed images[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Vancouver, 1989: 1005-1008. doi: 10.1109/IGARSS.1989.579061.
[10]
LEE J, HOPPEL K, and MANGO S. Unsupervised estimation of speckle noise in radar images[J]. International Journal of Imaging Systems and Technology, 1992, 4(4): 298-305. doi: 10.1002/ima.1850040409.
[11]
FOUCHER S, BOUCHER J, and BENIE G. Maximum likelihood estimation of the number of looks in SAR images in microwaves, radar and wireless communications[C]. 13th International Conference on MIKON-2000, 2000, 2: 657-660. doi: 10.1109/MIKON.2000.914020.
[12]
HU Dingsheng, ANFINSEN S, TAO Ding, et al. Investigation of variations in the equivalent number of looks for polarimetric channels[C]. International Workshop on Science and Applications SAR Polarimetry and Polarimetric Interferometry, Frascati, Rome, 2015.
[13]
OLIVER C and QUEGAN S. Understanding Synthetic Aperture Radar Images[M]. Raleigh, NC 27613: SciTech Publishing, Inc., 2004: 75-154.
[14]
FREITAS C, FRERY A, and CORREIA A. The polarimetric G distribution for SAR data analysis[J]. Environmetrics, 2005, 16(1): 13-31. doi: 10.1002/env.658.
[15]
ANFINSEN S. Statistical analysis of multilook polarimetric radar images with the Mellin transform[D]. [Ph.D. dissertation], University of Tromso, 2010.
[16]
LEE J, SCHULER D, LANG R, et al. K-distribution for multi-look processed polarimetric SAR imagery[C]. IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Pasadena, 1994: 2179-2181. doi: 10.1109/ IGARSS.1994.399685.
[17]
BOMBRUN L and BEAULIEU J. Fisher distribution for texture modeling of polarimetric SAR data[J]. IEEE Geoscience and Remote Sensing Letters, 2008, 5(3): 512-516. doi: 10.1109/LGRS.2008.923262.
[18]
ANFINSEN S and ELTOFT T. Application of the matrix- variate mellin transform to analysis of polarimetric radar images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2011, 49(6): 2281-2295. doi: 10.1109/TGRS.2010. 2103945.
[19]
ZHU Tingting, LI Fei, HEYGSTER G, et al. Antarctic sea-ice classification based on conditional random fields from RADARSAT-2 dual-polarization satellite images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2016, 9(6): 2451-2467. doi: 10.1109/ JSTARS.2016.2551318.
[20]
FORS A, BREKKE C, DOULGERIS A, et al. Late-summer sea ice segmentation with multi-polarisation SAR features in C and X band[J]. The Cryosphere, 2016, 10(1): 401-415. doi: 10.5194/tc-10-401-2016.
