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An Improved BAQ Encoding and Decoding Method for Improving the Quantized SNR of SAR Raw Data.

Wei Ji1,2,3, Xiaolan Qiu4,5, Xuejiao Wen6,7

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Summary

This study introduces an improved quantization method for Synthetic Aperture Radar (SAR) data. The new technique enhances image quality by improving performance when echo data is saturated.

Keywords:
anti-saturationblock adaptive quantization (BAQ)raw data compressionsignal-to-noise ratio (SNR)synthetic aperture radar (SAR)

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Area of Science:

  • Remote Sensing
  • Signal Processing
  • Data Compression

Background:

  • Block Adaptive Quantization (BAQ) is commonly used for Synthetic Aperture Radar (SAR) data.
  • Quantization saturation in SAR echo data degrades BAQ performance and imaging quality.

Purpose of the Study:

  • To propose an improved quantization method for saturated SAR echo data.
  • To enhance the performance of SAR imaging under quantization saturation conditions.

Main Methods:

  • An improved Lloyd-Max codec method is proposed.
  • The method involves modifying the codec look-up table for better quantization performance.

Main Results:

  • The proposed method reduces quantization power loss.
  • It improves the echo signal-to-noise ratio (SNR).
  • It mitigates the impact of quantization saturation on polarized SAR data scattering mechanisms.

Conclusions:

  • The improved Lloyd-Max codec offers better quantization performance for saturated SAR data.
  • The method has significant practical application value for SAR imaging.