一種基于小波變換的高倍數(shù)SAR原始數(shù)據(jù)壓縮算法
A Wavelet-Based Algorithm for SAR Raw Data Compression
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摘要: 該文提出了一種基于分塊提升小波變換的SAR原始數(shù)據(jù)壓縮算法。在該算法中，針對SAR原始數(shù)據(jù)特點，提出一種有效的小波子帶比特分配策略,為獲得最優(yōu)量化增益，在高比特率和低比特率兩種情況下，分別采用均勻和非均勻Lloyd-Max量化器對小波系數(shù)進行量化。實驗結(jié)果表明，該算法與傳統(tǒng)BAQ和BAVQ算法相比，在信噪比和圖像質(zhì)量等各方面指標都取得了明顯的改善。Abstract: In this paper, a technique for compressing Synthetic Aperture Radar(SAR) raw data using block lifting wavelet transform is considered. Due to the statistical properties of SAR signal, a proper subband bit allocation strategy is presented. At high bit rates and low bit rates, the uniform and non-uniform Lloyd-Max quantizer optimized for Gaussian statistics is respectively used to quantize the wavelet coefficients in order to get the optimum quantization gain. The performances achieved in terms of bit rate reduction and certain quality parameters have been evaluated. These show an increased performance in this method with respect to conventional methods.
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