Proceedings ArticleDOI
Advantages of Laplacian pyramids over ''à trous'' wavelet transforms for pansharpening of multispectral images
Bruno Aiazzi,Luciano Alparone,Stefano Baronti,Andrea Garzelli,Massimo Selva +4 more
- Vol. 8537, pp 853704
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TLDR
In this article, the advantages of generalized Laplacian pyramid (GLP) over the widespread "a trous" wavelet (ATW) transform for multispectral (MS) pansharpening based on multiresolution analysis (MRA) are investigated.Abstract:
The advantages provided by the generalized Laplacian pyramid (GLP) over the widespread “`a trous” wavelet (ATW)
transform for multispectral (MS) pansharpening based on multiresolution analysis (MRA) are investigated. The most
notable difference depends on the way GLP and ATW deal with aliasing possibly occurring in the MS data, which is
originated by insufficient sampling step size, or equivalently by a too high amplitude value of the modulation transfer
function (MTF) at Nyquist frequency and may generate annoying jagged patterns that survive in the sharpened image. In
this paper, it is proven that GLP is capable of compensating the aliasing of MS, unlike ATW, and analogously to component
substitution (CS) fusion methods, thanks to the decimation and interpolation stages present in its flowchart. Experimental
results will be presented in terms of quality/distortion global score indexes (SAM, ERGAS and Q4) for increasing amounts
of aliasing, measured by the amplitude at Nyquist frequency of the Gaussian-like lowpass filter simulating the average
MTF of the individual spectral channels of the instrument. GLP and ATW-based methods, both using the same MTF filters
and the same global injection gain, will be compared to show the advantages of GLP over ATW in the presence of aliasing
of the MS bands.read more
Citations
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Journal ArticleDOI
A Critical Comparison Among Pansharpening Algorithms
Gemine Vivone,Luciano Alparone,Jocelyn Chanussot,Mauro Dalla Mura,Andrea Garzelli,Giorgio Licciardi,Rocco Restaino,Lucien Wald +7 more
TL;DR: The authors attempt to fill the gap by providing a critical description and extensive comparisons of some of the main state-of-the-art pansharpening methods by offering a detailed comparison of their performances with respect to the different instruments.
Journal ArticleDOI
A New Benchmark Based on Recent Advances in Multispectral Pansharpening: Revisiting Pansharpening With Classical and Emerging Pansharpening Methods
Gemine Vivone,Mauro Dalla Mura,Andrea Garzelli,Rocco Restaino,Giuseppe Scarpa,Magnus O. Ulfarsson,Luciano Alparone,Jocelyn Chanussot +7 more
TL;DR: A new benchmark consisting of recent advances in MS pansharpening is proposed, and optimized classical approaches [multiresolution analysis (MRA) and component substitution (CS)] are compared with methods belonging to the third generation of panshARPening, represented by variational optimization-based (VO) and machine learning (ML) techniques.
Journal ArticleDOI
Pansharpening Based on Semiblind Deconvolution
Gemine Vivone,Miguel Simoes,Mauro Dalla Mura,Rocco Restaino,Jose M. Bioucas-Dias,Giorgio Licciardi,Jocelyn Chanussot +6 more
TL;DR: An algorithm for estimating the relation between PAN and MS images directly from the available data through an efficient optimization procedure is developed and is shown to outperform several very credited state-of-the-art approaches for the extraction of the details used in the current literature.
Journal ArticleDOI
A New Look at Image Fusion Methods from a Bayesian Perspective
Hankui K. Zhang,Bo Huang +1 more
TL;DR: A spectral consistency model is added in the Bayesian fusion framework to guarantee Wald’s spectral consistency with regard to arbitrary sensor point spread function, finding that the performance of the traditional EGIF methods improved significantly after adding the spectral consistencymodel.
Journal ArticleDOI
MTF-Adjusted Pansharpening Approach Based on Coupled Multiresolution Decompositions
TL;DR: A new fusion schema is proposed [coupled multiresolution decomposition model (CMD)], allowing the reconstruction of a high-resolution MS given its approximation and details obtained by MTF-tailored downsampling and wavelet decomposition, respectively.
References
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TL;DR: In this paper, it is shown that the difference of information between the approximation of a signal at the resolutions 2/sup j+1/ and 2 /sup j/ (where j is an integer) can be extracted by decomposing this signal on a wavelet orthonormal basis of L/sup 2/(R/sup n/), the vector space of measurable, square-integrable n-dimensional functions.
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TL;DR: In this paper, a review of Discrete-Time Multi-Input Multi-Output (DIMO) and Linear Phase Perfect Reconstruction (QLP) QMF banks is presented.
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The discrete wavelet transform: wedding the a trous and Mallat algorithms
TL;DR: It is shown that the commonly used Lagrange a trous filters are in one-to-one correspondence with the convolutional squares of the Daubechies filters for orthonormal wavelets of compact support.
Journal ArticleDOI
Multiresolution-based image fusion with additive wavelet decomposition
TL;DR: The authors developed a technique, based on multiresolution wavelet decomposition, for the merging and data fusion of high-resolution panchromatic and multispectral images which is clearly better than the IHS and LHS mergers in preserving both spectral and spatial information.