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Piecewise linear mapping algorithm for SAR raw data compression

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Abstract

When the saturation degree (SD) of space-borne SAR raw data is high, the performance of conventional block adaptive quantization (BAQ) deteriorates obviously. In order to overcome the drawback, this paper studies the mapping between the average signal magnitude (ASM) and the standard deviation of the input signal (SDIS) to the A/D from the original reference. Then, it points out the mistake of the mapping and introduces the concept of the standard deviation of the output signal (SDOS) from the A/D. After that, this paper educes the mapping between the ASM and SDOS from the A/D. Monte-Carlo experiment shows that none of the above two mappings is the optimal in the whole set of SD. Thus, this paper proposes the concept of piecewise linear mapping and the searching algorithm in the whole set of SD. According to the linear part, this paper gives the certification and analytical value of k and for nonlinear part, and utilizes the searching algorithm mentioned above to search the corresponding value of k. Experimental results based on simulated data and real data show that the performance of new algorithm is better than conventional BAQ when raw data is in heavy SD.

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References

  1. Kwok R, Johnson W T K. Block adaptive quantization of Magellan SAR data. IEEE Trans Geosci Remote Sens, 1989, 27(4): 375–383

    Article  Google Scholar 

  2. Yao S C, Wang Y F, Zhang B C, et al. Amplitude and phase compression algorithm for SAR raw data (in Chinese). J Electr Inf Tech, 2002, 24(11): 1627–1633

    Google Scholar 

  3. Jordan R L, Huneycutt B L. The SIR-C/X-SAR synthetic aperture radar system. IEEE Trans Geosci Remote Sens, 1995, 33(4): 829–839

    Article  Google Scholar 

  4. Boustani A E, Branham K, Kinsner W. A review of current raw SAR data compression. In: Canadian Conference on Electrical and Computer Engineering. Toronto Canada, May 2001. 925–930

  5. Benz U, Strodl K, Moreria A. A comparison of several algorithms for SAR raw data compression. IEEE Trans Geosci Remote Sens, 1994, 33(5): 1266–1276

    Article  Google Scholar 

  6. Mcleod I, Cumming I. ENVISAT ASAR data reduction: Impact on SAR interferometry. IEEE Trans Geosci Remote Sens, 1998, 36(2): 589–602

    Article  Google Scholar 

  7. Fischer J, Benz U, Moreira A. Efficient SAR raw data compression in frequency domain. In: Proceedings IGARSS’99. Hamburg Germany, 1999. 2261–2263

  8. Poggi G, Ragozini A R P, Verdoliva L. Compression of SAR data through range focusing and variable-rate vector quantization. IEEE Trans. Geosci Remote Sens, 2000, 38(3): 1282–1289

    Article  Google Scholar 

  9. Max J. Quantizing for Minimum Distortion. IRE Trans Inform Theory, 1960, 6: 7–12

    Article  MathSciNet  Google Scholar 

  10. Lloyd S. Least squares quantization in PCM. IEEE Trans Inform Theory, 1982, 28(2): 129–137

    Article  MATH  MathSciNet  Google Scholar 

  11. Zhao Y P, Wan F, Lei H. Compression on fractional saturation SAR raw data (in Chinese). J Electr Inform Tech, 2004, 26(3): 489–494

    Google Scholar 

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Authors and Affiliations

  1. Institute of Electronics, Chinese Academy of Sciences, Beijing, 100080, China

    HaiMing Qi, WeiDong Yu & Xi Chen

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  1. HaiMing Qi
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  2. WeiDong Yu
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  3. Xi Chen
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Correspondence to HaiMing Qi.

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Qi, H., Yu, W. & Chen, X. Piecewise linear mapping algorithm for SAR raw data compression. Sci. China Ser. F-Inf. Sci. 51, 2126–2134 (2008). https://doi.org/10.1007/s11432-008-0133-y

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  • DOI: https://doi.org/10.1007/s11432-008-0133-y

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