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Comparison between Mallat's and the 'a trous' discrete wavelet transform based algorithms for the fusion of multispectral and panchromatic images

机译:Mallat和基于“ trous”离散小波变换的多光谱和全色图像融合算法比较

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摘要

In the last few years, several researchers have proposed different procedures for the fusion of multispectral and panchromatic images based on the wavelet transform, which provide satisfactory high spatial resolution images keeping the spectral properties of the original multispectral data. The discrete approach of the wavelet transform can be performed with different algorithms, Mallat's and the 'a trous' being the most popular ones for image fusion purposes. Each algorithm has its particular mathematical properties and leads to different image decompositions. In this article, both algorithms are compared by the analysis of the spectral and spatial quality of the merged images which were obtained by applying several wavelet based, image fusion methods. All these have been used to merge Ikonos multispectral and panchromatic spatially degraded images. Comparison of the fused images is based on spectral and spatial characteristics and it is performed visually and quantitatively using statistical parameters and quantitative indexes. In spite of its a priori lower theoretical mathematical suitability to extract detail in a multiresolution scheme, the 'a trous' algorithm has worked out better than Mallat's algorithm for image merging purposes.
机译:在过去的几年中,几位研究人员提出了基于小波变换的多光谱和全色图像融合的不同方法,这些方法可提供令人满意的高空间分辨率图像,并保持原始多光谱数据的光谱特性。小波变换的离散方法可以用不同的算法执行,Mallat和“ trous”是用于图像融合的最受欢迎的算法。每种算法都有其特定的数学属性,并导致不同的图像分解。在本文中,通过分析通过应用几种基于小波的图像融合方法获得的合并图像的光谱和空间质量,比较了这两种算法。所有这些都已用于合并Ikonos多光谱和全色空间退化图像。融合图像的比较基于光谱和空间特征,并且使用统计参数和定量指标进行视觉和定量分析。尽管先验的理论数学适用于在多分辨率方案中提取细节的较低的理论数学适用性,但“ trous”算法在图像合并方面的效果比Mallat算法更好。

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