分块自适应量化算法对SAR原始数据功率损耗的影响

Hao-jie Zhang, Jie Chen, Hongcheng Zeng, Wei Yang, Jingwen Li
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引用次数: 1

摘要

为了提高合成孔径雷达(SAR)图像的辐射精度,分析了分块自适应量化(BAQ)对SAR原始数据造成的功率损失,并提出了一种补偿方法。首先定义了饱和因子γ - clip,然后利用归一化量化器的概念提出了统一的BAQ压缩模型。其次,在统一模型下推导了BAQ过程中的信号表达式,并将一些重要参数表示为γ - clip的函数。再次,通过γ - clip建立了压缩数据的饱和度与功率损耗的一一对应关系,并提出了相应的补偿方法。基于仿真数据的实验结果证明了理论关系的正确性和补偿方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of block adaptive quantization algorithm on power-loss with SAR raw data
In order to improve the radiometric precision of Synthetic Aperture Radar (SAR) image, this paper analyses the power-loss of SAR raw data which is caused by block adaptive quantization (BAQ) and then proposed a compensation method. Firstly, the saturation factor γclip is defined and then a unified model of BAQ compression is proposed by using the concept of normalized quantizer. Secondly, the signal expression during BAQ procedure is deduced under the unified model and some important parameters are expressed as a function of γclip. Thirdly, a one-to-one relationship between saturation degree and power-loss of compressed data is established through γclip, the corresponding compensation method is proposed as well. Experiment results based on simulated data prove the correctness of theoretical relationship and the validity of the compensation method.
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