基于多波段谱间预测的高光谱图像无损压缩算法

Hyperspectral Image Lossless Compression Algorithm Based on Multi-band Prediction

该文提出一种基于多波段谱间预测的高光谱图像无损压缩方案。首先,充分考虑到随着高光谱图像谱间分辨率的提高,其谱间相关性也越来越强烈,推导出由多个波段对当前波段做线性预测的预测器系数,然后给出快速计算求解预测器系数的算法。对AVIRIS图像进行压缩,实验结果表明,该算法压缩比高,运算速度快,具有极高的实用价值。

A hyperspectral image lossless compression algorithm based on multi-band prediction is proposed in this paper. Considering that as the spectral resolution of hyperspectral images increases, its spectral correlation becomes more and more significant, a group of prediction coefficients are derived, which are able to make use of multi-band to predict the current band linearly. And then a fast algorithm is given to solve the coefficients of the predictor. Experiments show that, with AVIRIS, the ratio of the algorithm is competitive and it runs fast, so it works efficiently in practice.