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Lossless coding of hyperspectral images through components ordering by minimum bidirected spanning tree

机译:通过最小双向生成树的组件通过组件的无损编码高光谱图像

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In this paper, we aim at improving the vector lifting scheme dedicated to lossless coding of hyperspectral images by an optimal components ordering. For this purpose, we propose a three-stage algorithm. The first one consists in classifying the spectral components into separate clusters sharing similar characteristics. Then, within each cluster, the problem of ordering the components for inter-component coding is addressed. It is formulated as the design of a minimum spanning tree whose vertices are the spectral components. Finally, at the last stage, the spatial and spectral redundancies are simultaneously exploited by a vector lifting scheme. Experiments carried out on AVIRIS images indicate the outperformance of the proposed method w.r.t. the state-of-art coders.
机译:在本文中,我们的目的是通过最佳分量来改善专用于富有无损图像无损编码的矢量提升方案。 为此,我们提出了一种三阶段算法。 第一个包括将光谱分量分类为分离共享类似特征的单独集群。 然后,在每个群集中,解决了对组件间编码进行排序的问题。 它被配制为设计最小生成树,其顶点是光谱分量。 最后,在最后阶段,通过矢量提升方案同时利用空间和光谱冗余。 在Aviris图像上进行的实验表明所提出的方法W.R.T的表现。 最先进的编码器。

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