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歸一化自適應(yīng)預(yù)測矢量量化算法壓縮SAR原始數(shù)據(jù)

關(guān)振紅,  朱岱寅,  朱兆達(dá)

關(guān)振紅, 朱岱寅, 朱兆達(dá). 歸一化自適應(yīng)預(yù)測矢量量化算法壓縮SAR原始數(shù)據(jù)[J]. 電子與信息學(xué)報, 2006, 28(3): 507-511.
引用本文: 關(guān)振紅, 朱岱寅, 朱兆達(dá). 歸一化自適應(yīng)預(yù)測矢量量化算法壓縮SAR原始數(shù)據(jù)[J]. 電子與信息學(xué)報, 2006, 28(3): 507-511.
Guan Zhen-hong, Zhu Dai-yin, Zhu Zhao-da. Compression of SAR Raw Data with Normalized Adaptive Predictive Vector Quantization[J]. Journal of Electronics & Information Technology, 2006, 28(3): 507-511.
Citation: Guan Zhen-hong, Zhu Dai-yin, Zhu Zhao-da. Compression of SAR Raw Data with Normalized Adaptive Predictive Vector Quantization[J]. Journal of Electronics & Information Technology, 2006, 28(3): 507-511.

歸一化自適應(yīng)預(yù)測矢量量化算法壓縮SAR原始數(shù)據(jù)

Compression of SAR Raw Data with Normalized Adaptive Predictive Vector Quantization

  • 摘要: 該文提出歸一化自適應(yīng)預(yù)測矢量量化(NAPVQ)算法壓縮SAR原始數(shù)據(jù)。NAPVQ算法先采用矢量線性預(yù)測器對輸入矢量進(jìn)行預(yù)測，再對原矢量與預(yù)測矢量之間的殘差矢量進(jìn)行矢量量化。該算法可視為差分脈沖調(diào)制在矢量量化中的拓展，其性能優(yōu)于塊自適應(yīng)量化(BAVQ)算法以及歸一化預(yù)測自適應(yīng)量化(NPAQ)算法。對算法復(fù)雜度的進(jìn)一步分析表明，NAPVQ算法能獲得復(fù)雜度和性能之間比較合理的折衷，具有實用價值。
    Abstract: This paper presents a new SAR raw data compression algorithm named Normalized Adaptive Predictive Vector Quantization (NAPVQ). The normalized SAR raw data are firstly processed with vector linear predictor, and then the error vectors are compressed with vector quantizer. Regarded as an extension of the differential pulse code modulation in the vector quantization, the NAPVQ achieves a better performance gain than the Block Adaptive Vector Quantization (BAVQ) and the Normalized Predictive Adaptive Quantization (NPAQ). With the analyses of algorithm complexity, the proposed algorithm shows a good performance/complexity trade-off and accommodates the requirement in engineering applications.
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  • Kwok R. Adaptive quantization of Magellan SAR data, IEEE Trans[J].on Geoscience and Remote Sensing.1989, 27(4):375-[2]Enrico M, Olmo G Lossy predictive coding of SAR raw data. IEEE Trans[J].on Geoscience and Remote Sensing.2003, 41(3):977-[3]Moreira A , Blaeser F. Fusion of block adaptive and vector quantization for efficient SAR data compression. IGARSS, Tokyo, 1993: 1583 - 1585.[4]楊云志, 黃順吉, 王建國. 矢量量化在SAR原始數(shù)據(jù)壓縮中應(yīng)用. 系統(tǒng)工程與電子技術(shù), 2002, 24(6): 42-44.[5]Owens J W, Marcellin M W, Hunt B R. Compression of synthetic aperture radar video phase history data using trellis-coded quantization techniques[J].IEEE Trans. on Geoscience and Remote Sensing.1999,37(2):1080-[6]Benz U, Strodl K, Moreia A. A comparison of several algorithms for SAR raw data compression[J].IEEE Trans. on Geoscience and Remote Sensing.1995,33(5):1266-[7][71 Pascazio V, Schirinzi G SAR raw data compression by subband coding. IEEE Trans. on Geoscience and Remote Sensing, 2003, 4l(2): 964 - 976.[8]孫圣和, 陸哲明. 矢量量化技術(shù)及應(yīng)用. 北京: 科學(xué)出版社, 2002: 116-136.[9][91 Jayant N S, Noll P. Digital Coding of Waveforms, NJ: Prentice-Hall, 1984,40 - 90.[10]Linde Y, Buzo A, Gray R. An algorithm for vector quantization design[J].IEEE Trans. on Communications.1980,28(1):84-[11]巍鐘銓. 合成孔徑雷達(dá)衛(wèi)星. 北京: 科學(xué)出版社, 2001: 202-210.
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出版歷程
  • 收稿日期:  2005-01-06
  • 修回日期:  2005-11-03
  • 刊出日期:  2006-03-19

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