Images fusion represents an important tool for remote sensing data elaborations. This technique is used for many purposes. Very often it is used to produce improved spatial resolution. The most common situation is represented by a pair of images: the first acquired by a multispectral sensor with a pixel size greater than the pixel size of the second image given by a panchromatic sensor. Starting from these images fusion produces a new multispectral image with a spatial resolution equal, or close to that of the panchromatic sensor. Very often fusion introduces important distortions on the pixel spectra. This fact could compromise the extraction of information from the image, especially when using an automatic algorithm based on spectral signature such as in the case of image classification. In this work we present the analysis of two fusion methods based on multiresolution decomposition obtained using the “a tròus” algorithm and applied to a pair of images acquired by TM and IRS-1C-PAN sensors. The methods studied are also compared with two classical fusion methods, the IHS and the SPC. Fused results are studied and compared using various tests including supervised classification. Most of the tests used have been extracted from literature regarding the assessment of spatial and spectral quality of fused images. This study show that the methods based on multiresolution decomposition outperform the classical fusion methods considered with respect to spectral content preservation. Moreover, it is shown that some of the quality tests are more significant than others. The discussion of this last aspect furnishes important indications for data quality assessment methods.

TM and IRS-1C-PAN data fusion using multiresolution decomposition methods based on the ‘a tròus’ algorithm / Teggi, Sergio; Cecchi, Rodolfo; Serafini, F.. - In: INTERNATIONAL JOURNAL OF REMOTE SENSING. - ISSN 0143-1161. - STAMPA. - 24:(2003), pp. 1287-1301.

TM and IRS-1C-PAN data fusion using multiresolution decomposition methods based on the ‘a tròus’ algorithm

TEGGI, Sergio;CECCHI, Rodolfo;
2003

Abstract

Images fusion represents an important tool for remote sensing data elaborations. This technique is used for many purposes. Very often it is used to produce improved spatial resolution. The most common situation is represented by a pair of images: the first acquired by a multispectral sensor with a pixel size greater than the pixel size of the second image given by a panchromatic sensor. Starting from these images fusion produces a new multispectral image with a spatial resolution equal, or close to that of the panchromatic sensor. Very often fusion introduces important distortions on the pixel spectra. This fact could compromise the extraction of information from the image, especially when using an automatic algorithm based on spectral signature such as in the case of image classification. In this work we present the analysis of two fusion methods based on multiresolution decomposition obtained using the “a tròus” algorithm and applied to a pair of images acquired by TM and IRS-1C-PAN sensors. The methods studied are also compared with two classical fusion methods, the IHS and the SPC. Fused results are studied and compared using various tests including supervised classification. Most of the tests used have been extracted from literature regarding the assessment of spatial and spectral quality of fused images. This study show that the methods based on multiresolution decomposition outperform the classical fusion methods considered with respect to spectral content preservation. Moreover, it is shown that some of the quality tests are more significant than others. The discussion of this last aspect furnishes important indications for data quality assessment methods.
24
1287
1301
TM and IRS-1C-PAN data fusion using multiresolution decomposition methods based on the ‘a tròus’ algorithm / Teggi, Sergio; Cecchi, Rodolfo; Serafini, F.. - In: INTERNATIONAL JOURNAL OF REMOTE SENSING. - ISSN 0143-1161. - STAMPA. - 24:(2003), pp. 1287-1301.
Teggi, Sergio; Cecchi, Rodolfo; Serafini, F.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

Licenza Creative Commons
I metadati presenti in IRIS UNIMORE sono rilasciati con licenza Creative Commons CC0 1.0 Universal, mentre i file delle pubblicazioni sono rilasciati con licenza Attribuzione 4.0 Internazionale (CC BY 4.0), salvo diversa indicazione.
In caso di violazione di copyright, contattare Supporto Iris

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11380/459350
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 60
  • ???jsp.display-item.citation.isi??? 49
social impact