2-D linear predictive compression of complex synthetic aperture radar (SAR) images

S. Marple
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Abstract

Current compression of complex SAR imagery uses line-by-line 1-D linear prediction which can cause discontinuities during reconstruction between lines. This paper introduces computationally fast full 2-D linear prediction techniques which can process entire complex SAR images (or sub-images) with another 10X factor improvement in complex data compression over 1-D techniques, while yielding better weak target and shadow area preservation. 2-D linear prediction also compresses linear extent target features not possible with 1-D algorithms.
复杂合成孔径雷达(SAR)图像的二维线性预测压缩
当前复杂SAR图像的压缩使用逐行1-D线性预测,这可能导致线间重建过程中的不连续。本文介绍了计算快速的全二维线性预测技术,该技术可以处理整个复杂的SAR图像(或子图像),在复杂数据压缩方面比一维技术提高10倍,同时产生更好的弱目标和阴影区域保存。二维线性预测还压缩了一维算法无法实现的线性范围目标特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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