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CORRELATION-BASED BAND ORDERING METHOD FOR LOSSLESS COMPRESSION OF HYPERSPECTRAL IMAGES

机译:高光谱图像无损压缩的基于相关带排序方法

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An efficient band ordering algorithm for lossless compression of hyperspectral images is presented in this paper. Main purpose of the proposed algorithm is to increase compression ratio dealing with hyperspectral images. At the first stage the algorithm considers interband correlation dependencies in a spectral image and uses them for optimal band ordering. Then linear prediction and entropy coding is applied for each image pixel. Band ordering based on correlation is shown to be an effective method for ordering of bands for lossless compression of hyperspectral images. The obtained results are very good, the achieved compression ratio is 1 percent better compared to the use of natural ordering for the image bands. Also the computation time is very short compared to the other band ordering methods.
机译:提出了一种高效的高光谱图像无损压缩的频带排序算法。该算法的主要目的是提高处理高光谱图像的压缩率。在第一阶段,该算法考虑频谱图像中的频带间相关性依赖性,并将其用于最佳频带排序。然后,将线性预测和熵编码应用于每个图像像素。基于相关性的频带排序被证明是一种用于对高光谱图像进行无损压缩的频带排序的有效方法。所获得的结果非常好,与对图像带使用自然排序相比,压缩率提高了1%。而且,与其他频带排序方法相比,计算时间非常短。

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