Automatic Radiometric Normalization of Multitemporal Satellite Imagery

Morton J. Canty; Allan Aasbjerg Nielsen; Michael Schmidt

doi:10.1016/j.rse.2003.10.024

Automatic Radiometric Normalization of Multitemporal Satellite Imagery

Morton J. Canty
, Allan Aasbjerg Nielsen
, Michael Schmidt

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Abstract

The linear scale invariance of the multivariate alteration detection (MAD) transformation is used to obtain invariant pixels for automatic relative radiometric normalization of time series of multispectral data. Normalization by means of ordinary least squares regression method is compared with normalization using orthogonal regression. The procedure is applied to Landsat TM images over Nevada, Landsat ETM+ images over Morocco, and SPOT HRV images over Kenya. Results from this new automatic, combined MAD/orthogonal regression method, based on statistical analysis of test pixels not used in the actual normalization, compare favorably with results from normalization from manually obtained time-invariant features.

Original language	English
Journal	Remote Sensing of Environment
Volume	91
Issue number	3-4
Pages (from-to)	441-451
ISSN	0034-4257
DOIs	https://doi.org/10.1016/j.rse.2003.10.024
Publication status	Published - 2004

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title = "Automatic Radiometric Normalization of Multitemporal Satellite Imagery",

abstract = "The linear scale invariance of the multivariate alteration detection (MAD) transformation is used to obtain invariant pixels for automatic relative radiometric normalization of time series of multispectral data. Normalization by means of ordinary least squares regression method is compared with normalization using orthogonal regression. The procedure is applied to Landsat TM images over Nevada, Landsat ETM+ images over Morocco, and SPOT HRV images over Kenya. Results from this new automatic, combined MAD/orthogonal regression method, based on statistical analysis of test pixels not used in the actual normalization, compare favorably with results from normalization from manually obtained time-invariant features.",

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AU - Nielsen, Allan Aasbjerg

AU - Schmidt, Michael

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AB - The linear scale invariance of the multivariate alteration detection (MAD) transformation is used to obtain invariant pixels for automatic relative radiometric normalization of time series of multispectral data. Normalization by means of ordinary least squares regression method is compared with normalization using orthogonal regression. The procedure is applied to Landsat TM images over Nevada, Landsat ETM+ images over Morocco, and SPOT HRV images over Kenya. Results from this new automatic, combined MAD/orthogonal regression method, based on statistical analysis of test pixels not used in the actual normalization, compare favorably with results from normalization from manually obtained time-invariant features.

U2 - 10.1016/j.rse.2003.10.024

DO - 10.1016/j.rse.2003.10.024

M3 - Journal article

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SP - 441

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JO - Remote Sensing of Environment

JF - Remote Sensing of Environment

IS - 3-4

ER -

Automatic Radiometric Normalization of Multitemporal Satellite Imagery

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