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Wavelet based image fusion techniques — An introduction, review and comparison

机译:基于小波的图像融合技术—简介,评论与比较

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摘要

Image fusion involves merging two or more images in such a way as to retain the most desirable characteristics of each. When a panchromatic image is fused with multispectral imagery, the desired result is an image with the spatial resolution and quality of the panchromatic imagery and the spectral resolution and quality of the multispectral imagery. Standard image fusion methods are often successful at injecting spatial detail into the multispectral imagery but distort the colour information in the process. Over the past decade, a significant amount of research has been conducted concerning the application of wavelet transforms in image fusion. In this paper, an introduction to wavelet transform theory and an overview of image fusion technique are given, and the results from a number of wavelet-based image fusion schemes are compared. It has been found that, in general, wavelet-based schemes perform better than standard schemes, particularly in terms of minimizing colour distortion. Schemes that combine standard methods with wavelet transforms produce superior results than either standard methods or simple wavelet-based methods alone. The results from wavelet-based methods can also be improved by applying more sophisticated models for injecting detail information; however, these schemes often have greater set-up requirements.
机译:图像融合涉及以保留每个图像最理想的特性的方式合并两个或多个图像。当全色图像与多光谱图像融合时,期望的结果是具有全色图像的空间分辨率和质量以及多光谱图像的光谱分辨率和质量的图像。标准图像融合方法通常可以成功地将空间细节注入多光谱图像中,但会在处理过程中使颜色信息失真。在过去的十年中,已经进行了大量有关小波变换在图像融合中的应用的研究。本文介绍了小波变换理论并概述了图像融合技术,并比较了多种基于小波的图像融合方案的结果。已经发现,通常,基于小波的方案比标准方案表现更好,特别是在最小化颜色失真方面。与标准方法或简单的基于小波的方法相比,将标准方法与小波变换相结合的方案可产生更好的结果。通过应用更复杂的模型来注入细节信息,基于小波方法的结果也可以得到改善。但是,这些方案通常具有更高的设置要求。

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