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Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis (Articolo in rivista)
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- Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis (Articolo in rivista) (literal)
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- 2002-01-01T00:00:00+01:00 (literal)
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- 10.1109/TGRS.2002.803623 (literal)
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Bruno Aiazzi; Luciano Alparone; Stefano Baronti; Andrea Garzelli (2002)
Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis
in IEEE transactions on geoscience and remote sensing; IEEE-Institute Of Electrical And Electronics Engineers Inc., Piscataway (Stati Uniti d'America)
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- Bruno Aiazzi; Luciano Alparone; Stefano Baronti; Andrea Garzelli (literal)
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- Special Issue on the 2001 International Geoscience and Remote Sensing Symposium (IGARSS '01), Sydney, Australia, 9-13 Luglio 2001: Scanning the present and resolving the future (literal)
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- Institute of Applied Physics \"N. Carrara,\" National Research Council (IFAC-CNR), I-50127 Florence, Italy
Department of Electronics and Telecommunications, University of Florence, I-50139 Florence, Italy
Institute of Applied Physics \"N. Carrara,\" National Research Council (IFAC-CNR), I-50127 Florence, Italy
Department of Information Engineering, University of Siena, I-53100 Siena, Italy (literal)
- Titolo
- Context-driven fusion of high spatial and spectral resolution images based on oversampled multiresolution analysis (literal)
- Abstract
- This paper compares two general and formal solutions to the problem of fusion of multispectral images with high-resolution panchromatic observations. The former exploits the undecimated discrete wavelet transform, which is an octave bandpass representation achieved from a conventional discrete wavelet transform by omitting all decimators and upsampling the wavelet filter bank. The latter relies on the generalized Laplacian pyramid, which is another oversampled structure obtained by recursively subtracting from an image an expanded decimated lowpass version. Both the methods selectively perform spatial-frequencies spectrum substitution from an image to another. In both schemes, context dependency is exploited by thresholding the local correlation coefficient between the images to be merged, to avoid injection of spatial details that are not likely to occur in the target image. Unlike other multiscale fusion schemes, both the present decompositions are not critically subsampled, thus avoiding possible impairments in the fused images, due to missing cancellation of aliasing terms. Results are presented and discussed on SPOT data. (literal)
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