Dept. of Electr. Eng., New South Wales Univ., Canberra, ACT.
IEEE Trans Image Process. 1996;5(5):713-9. doi: 10.1109/83.495955.
Adaptive DPCM methods using linear prediction are described for the lossless compression of hyperspectral (224-band) images recorded by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The methods have two stages-predictive decorrelation (which produces residuals) and residual encoding. Good predictors are described, whose performance closely approaches limits imposed by sensor noise. It is imperative that these predictors make use of the high spectral correlations between bands. The residuals are encoded using variable-length coding (VLC) methods, and compression is improved by using eight codebooks whose design depends on the sensor's noise characteristics. Rice (1979) coding has also been evaluated; it loses 0.02-0.05 b/pixel compression compared with better VLC methods but is much simpler and faster. Results for compressing ten AVIRIS images are reported.
描述了用于机载可见/红外成像光谱仪（AVIRIS）记录的高光谱（224 波段）图像无损压缩的基于线性预测的自适应差分脉冲编码调制（DPCM）方法。该方法有两个阶段——预测去相关（产生残差）和残差编码。描述了性能接近传感器噪声限制的良好预测器。这些预测器必须利用波段之间的高光谱相关性。使用变长编码（VLC）方法对残差进行编码，并通过使用八个码本来提高压缩率，这些码本的设计取决于传感器的噪声特性。还评估了 Rice（1979）编码；与更好的 VLC 方法相比，它损失了 0.02-0.05 b/像素的压缩，但它更简单、更快。报告了压缩十个 AVIRIS 图像的结果。
