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An Optimization-Based Approach to Fusion of Hyperspectral Images

机译:基于优化的高光谱图像融合方法

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摘要

In this paper we propose a new approach for visualization-oriented fusion of hyperspectral image bands. The proposed technique has been devised to generate the fused image with a certain set of desired properties for a better visualization. The fusion technique should provide a resultant image with a high local contrast without driving individual pixels into over- or under-saturation. We focus on these desired properties of the resultant image, and formulate a multi-objective cost function for the same. We have shown how we can incorporate the constraint of spatial smoothness of the weight vectors, as opposed to the smoothness of the fused image. The solution of this optimization problem has been provided using the Euler–Lagrange technique. By using an appropriate auxiliary variable, we show how the constrained optimization problem can be converted into a computationally efficient unconstrained one. The effectiveness of the proposed technique is substantiated from the visual and quantitative results provided.
机译:在本文中,我们提出了一种面向可视化的高光谱图像带融合的新方法。已经设计出所提出的技术以产生具有一组期望特性的融合图像,以实现更好的可视化。融合技术应提供具有高局部对比度的合成图像,而不会使单个像素变得过饱和或过饱和。我们着重于所得图像的这些所需属性,并为该图像制定一个多目标成本函数。我们已经展示了如何结合权向量的空间平滑性约束,而不是融合图像的平滑性。使用欧拉-拉格朗日技术提供了此优化问题的解决方案。通过使用适当的辅助变量,我们说明了如何将约束优化问题转换为计算有效的无约束变量。所提供的视觉和定量结果证实了所提出技术的有效性。

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