Hyperspectral images are generated by collecting hundreds of narrow and contiguously spaced spectral bands of data producing a highly correlated long sequence of images. Some application specific data compression techniques may be applied advantageously before we process, store or transmit hyperspectral images. This paper applies asymmetric tree 3DSPIHT (AT-3DSPIHT) for hyperspectral image compression; it also investigates and compares the performance of the AT-3DSPIHT, 3DSPIHT and 3DSPECK on hyperspectral image compression. Results show that the AT-3DSPIHT outperforms the other two by the approximate range of 0.2 to 0.9 dB PSNR. It guarantees over 4 dB PSNR improvement at all rates or rate savings at least a factor of 2.5 over 2D coding of separate spectral bands without axial transformation.
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机译：通过收集产生高度相关的长序列图像的数据的数百个窄且连续间隔的频谱频带来产生高光谱图像。在我们处理，存储或发送超光谱图像之前，可以有利地应用一些特定的数据压缩技术。本文适用于高光谱图像压缩的非对称树3dspiht（at-3dspiht）;它还调查和比较AT-3DSPIHT，3DSPIHT和3DSPECK对高光谱图像压缩的性能。结果表明，AT-3DSPIHT通过0.2至0.9dB PSN的近似范围优于其他两个。它保证了所有速率的4 dB PSNR改进，或节省至少2.5倍，在没有轴向变换的单独光谱带上的2D编码中至少为2.5。
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