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Multiscale algorithms for joint detection and compression in SAR imagery

机译:SAR图像中联合检测和压缩的多尺度算法

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Abstract: We present a novel content-adaptive multiresolution SAR image formation processing algorithm that incorporates dynamic, on-line detection algorithms into the image formation process. The idea is to vary image resolution locally depending on scene content, focusing the SAR imagery to fine resolution only in regions where the scene reflectivity varies rapidly, while forming the rest of the image at coarser resolution or with reduced fidelity. Our `decision-directed' SAR image formation algorithm may have applications in systems where on-board processing or datalink constraints limits the area coverage rates or resolution. We present examples of this multiresolution SAR processing on SAR imagery and show that compression rates on the order of 70:1 or more (i.e., 0.45 bits/pixel starting from 32 bits/complex sample, 16 bits/I, 16 bits/Q), can be obtained while still preserving coherent target signatures and with minor degradation in perceptual image quality.!14
机译:摘要:我们提出了一种新颖的内容自适应多分辨率SAR图像形成处理算法,该算法将动态的在线检测算法整合到了图像形成过程中。想法是根据场景内容在本地更改图像分辨率,仅在场景反射率变化迅速的区域将SAR图像聚焦到较高分辨率,而其余图像则以较粗糙的分辨率或降低的保真度形成。我们的“决策导向” SAR图像形成算法可能在车载处理或数据链路约束限制了区域覆盖率或分辨率的系统中得到应用。我们在SAR图像上提供了这种多分辨率SAR处理的示例,并显示了70:1或更高的压缩率(即,从32位/复杂样本,16位/ I,16位/ Q开始的0.45位/像素)可以在保持相干目标特征且感知图像质量稍有下降的同时获得!14

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