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Sentinel-1 Data Border Noise Removal and Seamless Synthetic Aperture Radar Mosaic Generation

机译:Sentinel-1数据边界噪声消除和无缝合成孔径雷达马赛克生成

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The Canadian Ice Service (CIS, Ottawa, ON, Canada) is receiving hundreds of Synthetic Aperture Radar (SAR) images daily with almost a complete coverage of Canada navigable waters for the monitoring and mapping of seasonal sea and lake ice. In order to efficiently use and analyze such a large amount and wide areal extent of data, short-term (i.e., 12 h to a few days) highresolution mosaic products are of interest. Among these SAR images, Sentinel-1 data have been known to have an issue of border noise which needs to be removed before generating a seamless mosaic. A method using line-by-line scanning and filtering is proposed, which traces an extreme jump between two neighboring pixels along every scan line. The results show that this method can remove the noise precisely while retaining the rest of the valid data. For visual display, analysis, and interpretation, as done at the CIS, a tone-balanced smooth mosaic is of interest and value to ice analysts in displaying the overall ice distribution and in viewing and comparing cross-region ice conditions. To address this, a scene boundary match balancing method is developed. These shortterm mosaic products are proved very helpful in daily ice analysis and macroscopic ice drift measurement.
机译:加拿大冰服务局(加拿大安大略省渥太华的独联体)每天接收数百张合成孔径雷达(SAR)图像,几乎完整覆盖了加拿大通航水域,以监测和绘制季节性海冰和湖泊冰图。为了有效地使用和分析如此大量和广泛的数据范围,关注短期(即12小时到几天)高分辨率马赛克产品。在这些SAR图像中,已知Sentinel-1数据存在边界噪声问题,需要在生成无缝拼接之前将其消除。提出了一种使用逐行扫描和滤波的方法,该方法跟踪沿着每条扫描线的两个相邻像素之间的极端跳跃。结果表明,该方法可以准确地消除噪声,同时保留其余有效数据。对于视觉显示,分析和解释(如在CIS上所做的那样),色调平衡的平滑马赛克对于冰分析人员在显示总体冰分布以及查看和比较跨区域冰况方面具有重要意义和价值。为了解决这个问题,开发了场景边界匹配平衡方法。这些短期镶嵌产品被证明对日常冰分析和宏观冰漂移测量非常有帮助。

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