基于QNR优化约束的高光谱泛锐化

2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing Pub Date : 2009-10-16 DOI:10.1109/WHISPERS.2009.5289027

M. Khan, J. Chanussot, L. Alparone

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引用次数: 9

摘要

提出了一种低分辨率高光谱(HS)图像的泛锐化方法。该方法在优化QNR质量评价指标的光谱质量准则和空间质量准则的基础上提出。利用进化算法得到的Pareto解，实现了光谱约束和空间质量约束的同时优化。定义了从Pareto解中选择单个解的选择准则，所得结果与现有的泛锐化方法相比，在定性和定量上都有提高。

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Hyperspectral pansharpening using QNR optimization constraint

This paper presents a method for pansharpening of low resolution Hyperspectral (HS) images. The proposed method is based upon the optimization of both the spectral and spatial quality criteria of the QNR quality assessment index. The simultaneous optimization of the spectral and spatial quality constraints is obtained by means of the Pareto solutions, obtained by making use of an evolutionary algorithm. A selection criteria is defined to select a single solution from among the Pareto solutions and the results obtained show both quantitative and qualitative improvement over the results obtained by some existing pansharpening methods.

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来源期刊

2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing

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