A Scalloping Correction Method for ScanSAR Image Based on Improved Kalman Filter Model
-
摘要: 星载扫描合成孔径雷达(ScanSAR)采取Burst工作模式，该模式在获得宽幅测绘能力的同时，也导致图像中产生了固有的扇贝效应，严重影响图像的视觉效果和定量应用。该文结合对ScanSAR图像方位向统计特性的分析，针对现有滤波模型稳定性差和时间复杂度高等缺点，提出了一种改进的Kalman滤波模型，对图像方位向标准差和均值进行滤波以校正扇贝条纹。在高分三号(GF-3)卫星获取的真实ScanSAR图像上的校正结果验证了改进算法的有效性和高效性，此外在建筑群和海陆交界等复杂场景图像上的实验结果表明，改进算法具有较强的鲁棒性。Abstract: The spaceborne Scanning Synthetic Aperture Radar (ScanSAR) adopts the Burst working mode. While obtaining wide-range mapping capabilities, this mode also causes an inherent scalloping in the image, which seriously affects the visual effects and quantitative applications of the image. Based on the analysis of the azimuth statistical characteristics of ScanSAR images and aimed at the shortcomings of the existing filtering model such as poor stability and high time complexity, an improved Kalman filtering model is proposed, which filters the standard deviation and mean of image in azimuth position to correct scallop stripes. The correction results on the real ScanSAR images acquired by the GF-3 satellite verify the effectiveness and efficiency of the improved algorithm. Furthermore, the experimental results on complex scene images such as buildings and the junction of sea and land indicate that the strong robustness of the improved algorithm.
-
表 1 扇贝效应强度量化比较(dB)
扇贝效应 最大值 最小值 平均值 标准差 校正前 2.66 1.71 2.01 0.19 Iqbal算法 0.76 0.15 0.46 0.13 谷昕炜算法 1.63 0.52 0.94 0.21 本文算法 0.48 0.03 0.22 0.11 
下载: 导出CSV
-
[1] 张庆君. 高分三号卫星总体设计与关键技术[J]. 测绘学报, 2017, 46(3): 269–277. doi: 10.11947/j.AGCS.2017.20170049ZHANG Qingjun. System design and key technologies of the GF-3 satellite[J]. Acta Geodaetica et Cartographica Sinica, 2017, 46(3): 269–277. doi: 10.11947/j.AGCS.2017.20170049 [2] BAMLER R. Optimum look weighting for burst-mode and ScanSAR processing[J]. IEEE Transactions on Geoscience and Remote Sensing, 1995, 33(3): 722–725. doi: 10.1109/36.387587 [3] VIGNERON C M. Radiometric image quality improvement of ScanSAR data[D]. [Master dissertation], University of British Columbia, 1996. doi: 10.14288/1.0065108. [4] SHIMADA M. Long-term stability of L-band normalized radar cross section of Amazon rainforest using the JERS-1 SAR[J]. Canadian Journal of Remote Sensing, 2005, 31(1): 132–137. doi: 10.5589/m04-058 [5] SHIMADA M. A new method for correcting ScanSAR scalloping using forests and inter-SCAN banding employing dynamic filtering[J]. IEEE Transactions on Geoscience and Remote Sensing, 2009, 47(12): 3933–3942. doi: 10.1109/TGRS.2009.2027596 [6] 张晓, 仇晓兰, 仲利华, 等. 基于系统噪声抑制的ScanSAR辐射校正方法[J]. 国外电子测量技术, 2015, 34(6): 47–51. doi: 10.19652/j.cnki.femt.2015.06.011ZHANG Xiao, QIU Xiaolan, ZHONG Lihua, et al. Radiometric correction algorithm for ScanSAR scalloping based on reduction of system noise[J]. Foreign Electronic Measurement Technology, 2015, 34(6): 47–51. doi: 10.19652/j.cnki.femt.2015.06.011 [7] ROMEISER R, HORSTMANN J, and GRABER H. A new algorithm for descalloping ScanSAR images by post processing[C]. ESA Living Planet Symposium, Bergen, Norway, 2010: 354–358. [8] ROMEISER R, HORSTMANN J, CARUSO M J, et al. A descalloping postprocessor for ScanSAR images of ocean scenes[J]. IEEE Transactions on Geoscience and Remote Sensing, 2013, 51(6): 3259–3272. doi: 10.1109/TGRS.2012.2222648 [9] SCHIAVULLI D, SORRENTINO A, and MIGLIACCIO M. An innovative technique for postprocessing descalloping[J]. IEEE Geoscience and Remote Sensing Letters, 2012, 10(3): 424–427. doi: 10.1109/LGRS.2012.2207879 [10] IQBAL M, CHEN Jie, YANG Wei, et al. Kalman filter for removal of scalloping and inter-scan banding in scanSAR images[J]. Progress in Electromagnetics Research, 2012, 132: 443–461. doi: 10.2528/PIER12082107 [11] IQBAL M and CHEN Jie. Removal of scalloping in ScanSAR images using Kalman filter[C]. 2012 IEEE International Geoscience and Remote Sensing Symposium, Munich, Germany, 2012: 260–263. doi: 10.1109/IGARSS.2012.6351588. [12] 谷昕炜, 杨威, 陈杰. 海陆交界非平稳场景星载ScanSAR扇贝效应抑制方法[J]. 海军航空工程学院学报, 2018, 33(1): 125–129, 134. doi: 10.7682/j.issn.1673-1522.2018.01.005GU Xinwei, YANG Wei, and CHEN Jie. Suppression of scalloping effects in spaceborne ScanSAR images for non-stationary scene of coastal area monitoring[J]. Journal of Naval Aeronautical and Astronautical University, 2018, 33(1): 125–129, 134. doi: 10.7682/j.issn.1673-1522.2018.01.005 [13] CUMMING I G, WONG F H, 洪文, 胡东辉译. 合成孔径雷达成像: 算法与实现[M]. 北京: 电子工业出版社, 2012: 285–286.CUMMING I G, WONG F H, HONG Wen, HU Donghui. translation. Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation[M]. Beijing: Publishing House of Electronics Industry, 2012: 285–286. [14] PELI E. Contrast in complex images[J]. Journal of the Optical Society of America A, 1990, 7(10): 2032–2040. doi: 10.1364/JOSAA.7.002032 [15] HAWKINS R K and VACHON P W. Modelling SAR scalloping in burst mode products from RadarSAT-1 and ENVISAT[C]. The CEOS Working Group on Calibration/Validation SAR Workshop, London, United Kingdom, 2002: 24–26. [16] 胡炎, 单子力, 高峰. 基于增强指数加权均值比的SAR图像边缘检测算法[J]. 电子与信息学报, 2018, 40(5): 1166–1172. doi: 10.11999/JEIT170806HU Yan, SHAN Zili, and GAO Feng. Edge detection algorithm for SAR image based on enhanced ROEWA[J]. Journal of Electronics &Information Technology, 2018, 40(5): 1166–1172. doi: 10.11999/JEIT170806 [17] 陈祥, 孙俊, 尹奎英, 等. 基于Otsu与海域统计特性的SAR图像海陆分割算法[J]. 数据采集与处理, 2014, 29(4): 603–608. doi: 10.3969/j.issn.1004-9037.2014.04.017CHEN Xiang, SUN Jun, YIN Kuiying, et al. Sea-land segmentation algorithm of SAR image based on Otsu method and statistical characteristic of sea area[J]. Journal of Data Acquisition and Processing, 2014, 29(4): 603–608. doi: 10.3969/j.issn.1004-9037.2014.04.017 [18] CHENG Dongcai, MENG Gaofeng, XIANG Shiming, et al. Efficient sea–land segmentation using seeds learning and edge directed graph cut[J]. Neurocomputing, 2016, 207: 36–47. doi: 10.1016/j.neucom.2016.04.020 [19] LEI Sen, ZOU Zhengxia, LIU Dunge, et al. Sea-land segmentation for infrared remote sensing images based on superpixels and multi-scale features[J]. Infrared Physics & Technology, 2018, 91: 12–17. doi: 10.1016/j.infrared.2018.03.012 [20] 肖乐意, 欧阳红林, 范朝冬. 基于记忆分子动理论优化算法的多目标截面投影Otsu图像分割[J]. 电子与信息学报, 2018, 40(1): 189–199. doi: 10.11999/JEIT170301XIAO Leyi, OUYANG Honglin, and FAN Chaodong. Multi-objective cross section projection Otsu’s method based on memory knetic-molecular theory optimization algorithm[J]. Journal of Electronics &Information Technology, 2018, 40(1): 189–199. doi: 10.11999/JEIT170301 -
图(8) / 表(2)
计量
- 文章访问数: 1387
- HTML全文浏览量: 567
- PDF下载量: 110
- 被引次数: 0
下载:
