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Sub-pixellic Methods for Sidelobes Suppression and Strong Targets Extraction in Single Look Complex SAR Images

机译:单视复杂saR图像中旁瓣去除和强目标提取的亚像素方法

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摘要

SAR images display very high dynamic ranges. Man-made structures (like buildings or power towers) produce echoes that are several orders of magnitude stronger than echoes from diffusing areas (vegetated areas) or from smooth surfaces (e.g., roads). The impulse response of the SAR imaging system is thus clearly visible around the strongest targets: sidelobes spread over several pixels, masking the much weaker echoes from the background. To reduce the sidelobes of the impulse response, images are generally spectrally apodized, trading resolution for a reduction of the sidelobes. This apodization procedure (global or shift-variant) introduces spatial correlations in the speckle-dominated areas which complicates the design of estimation methods. This paper describes strategies to cancel sidelobes around point-like targets while preserving the spatial resolution and the statistics of speckle-dominated areas. An irregular sampling grid is built to compensate the sub-pixel shifts and turn cardinal sines into discrete Diracs. A statistically grounded approach for point-like target extraction is also introduced, thereby providing a decomposition of a single look complex image into two components: a speckle-dominated image and the point-like targets. This decomposition can be exploited to produce images with improved quality (full resolution and suppressed sidelobes) suitable both for visual inspection and further processing (multi-temporal analysis, despeckling, interferometry).
机译:SAR图像显示很高的动态范围。人造结构(例如建筑物或电力塔)产生的回声比扩散区域(植被区域)或光滑表面(例如道路)产生的回声要强几个数量级。因此,SAR成像系统的脉冲响应在最强的目标周围清晰可见:旁瓣分布在几个像素上,掩盖了来自背景的弱得多的回波。为了减少脉冲响应的旁瓣,通常在频谱上对图像进行变迹,以降低旁瓣的分辨率为代价。这种切趾程序(全局或移位变量)在斑点为主的区域中引入了空间相关性,这使估计方法的设计变得复杂。本文介绍了在保留空间分辨率和斑点为主区域统计信息的同时消除点状目标周围旁瓣的策略。建立了不规则的采样网格,以补偿子像素的偏移并将基波正弦转换为离散的狄拉克(Diracs)。还介绍了一种基于统计的点状目标提取方法,从而将单个外观复杂的图像分解为两个部分:斑点为主的图像和点状目标。可以利用这种分解来产生具有改进的质量(全分辨率和抑制的旁瓣)的图像,该图像既适合视觉检查,又适合进一步处理(多时间分析,去斑点,干涉测量)。

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