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Image fusion is a critical issue for remote sensing, and many algorithms have been developed. Image quality assessment of fused image might provide comparison between fusion methods, but the conclusio...
While many remote sensing and GIS applications require both the spatial resolution and spectral resolution be high, image fusion, or in other words, image sharpening, is a useful technique. To date, n...
The main objective of the remotely sensed data fusion is to create an integrated composite image of improved information and enhanced interpretability. This data have geospatial details about earth’s ...
Against the Spectrum distortion problem of the IHS method which exists in the Quick-Bird data fusion, the paper proposes visualpan band method and Linear weighted matching two methods to improve it, p...
Pan sharpening methods aim to produce a more informative image containing the positive aspects of both source images. However, the pan sharpening process usually introduces some spectral and spatial d...
The traditional IHS fusion, as a spatial domain method, mostly achieves the good spatial quality but the spectral distortion. The discrete fractional random transform (DFRNT) fusion, as a transform ...
针对IHS变换在QuickBird数据融合中存在的光谱扭曲问题,提出了利用Visual-Pan波段和线性加权匹配两种方法进行改进 ,并给出了Visual-Pan波段方法中系数α的最佳取值范围,以及线性加权匹配融合图像的空间特征与光谱特征达到最佳效果时Pan 权值(wPan)和I权值(wI)的最佳取值。结果表明,对于Visual-Pan方法而言,当0.2<α<0.25时,可以获得非常好的融合效果...
探讨了遥感多光谱与全色波段图像的融合问题,分析了基于IHS变换的小波包变换分解的遥感图像融合方法,提出了基于最优树分解的融合方法。此方法首先将多光谱图像进行IHS变换,然后对I分量和全色图像进行小波包分解和最优树分解,再进行融合,最后进行IHS 逆变换得到融合图像。此方法不仅得到较好的图像主观视觉效果,而且兼顾了客观上熵最大的原则。

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