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首頁(yè)> 外文期刊>International journal of remote sensing >Comparison between Mallat's and the 'a trous' discrete wavelet transform based algorithms for the fusion of multispectral and panchromatic images
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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

機(jī)譯：Mallat和基于“ trous”離散小波變換的多光譜和全色圖像融合算法比較

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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.
機(jī)譯：在過(guò)去的幾年中，幾位研究人員提出了基于小波變換的多光譜和全色圖像融合的不同方法，這些方法可提供令人滿意的高空間分辨率圖像，并保持原始多光譜數(shù)據(jù)的光譜特性。小波變換的離散方法可以用不同的算法執(zhí)行，Mallat和“ trous”是用于圖像融合的最受歡迎的算法。每種算法都有其特定的數(shù)學(xué)屬性，并導(dǎo)致不同的圖像分解。在本文中，通過(guò)分析通過(guò)應(yīng)用幾種基于小波的圖像融合方法獲得的合并圖像的光譜和空間質(zhì)量，比較了這兩種算法。所有這些都已用于合并Ikonos多光譜和全色空間退化圖像。融合圖像的比較基于光譜和空間特征，并且使用統(tǒng)計(jì)參數(shù)和定量指標(biāo)進(jìn)行視覺(jué)和定量分析。盡管先驗(yàn)的理論數(shù)學(xué)適用于在多分辨率方案中提取細(xì)節(jié)的較低的理論數(shù)學(xué)適用性，但“ trous”算法在圖像合并方面的效果比Mallat算法更好。

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