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Interpreting image-based methods for estimating the signal-to-noise ratio

Interpreting image-based methods for estimating the signal-to-noise ratio
Interpreting image-based methods for estimating the signal-to-noise ratio
The signal-to-noise ratio (SNR) of remotely sensed imagery has been estimated directly using a variety of image-based methods such as the Homogeneous Area (HA) and Geostatistical (GS) methods. However, previous research has shown that such estimates may be dependent on land cover type. We examine this dependence on land cover type using Compact Airborne Spectrographic Imager (CASI) imagery of an agricultural region in Falmouth, Cornwall. The SNR was estimated using the GS method for six different land covers and a range of wavelengths. Large differences in the SNR existed between land cover types. It follows that single estimates of SNR (e.g. for one land cover) should not be associated with an image (as a whole). It is recommended that either (i) each statistic is reported per land cover type per wavelength or (ii) that an image of local statistics is reported per wavelength. The regression of noise on signal can be used to separate independent noise (intercept) from signal-dependent noise (slope). Variation in the noise and SNR estimates can be used to (i) allow more accurate prediction of the SNR and (ii) provide information on uncertainty.
aerial photography - geography, environmental sciences, remote sensing
0143-1161
5099-5115
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Sargent, I.M.J.
0a0121d8-fa33-49d3-9675-76ed31b798f4
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Williams, J.
2ab33bc3-4988-493b-9cd5-ac68d28385cb
Atkinson, P.M.
96e96579-56fe-424d-a21c-17b6eed13b0b
Sargent, I.M.J.
0a0121d8-fa33-49d3-9675-76ed31b798f4
Foody, G.M.
06e50027-603d-4a5b-88f5-af2bb6235a37
Williams, J.
2ab33bc3-4988-493b-9cd5-ac68d28385cb

Atkinson, P.M., Sargent, I.M.J., Foody, G.M. and Williams, J. (2005) Interpreting image-based methods for estimating the signal-to-noise ratio. International Journal of Remote Sensing, 26 (20), 5099-5115. (doi:10.1080/01431160500254999).

Record type: Article

Abstract

The signal-to-noise ratio (SNR) of remotely sensed imagery has been estimated directly using a variety of image-based methods such as the Homogeneous Area (HA) and Geostatistical (GS) methods. However, previous research has shown that such estimates may be dependent on land cover type. We examine this dependence on land cover type using Compact Airborne Spectrographic Imager (CASI) imagery of an agricultural region in Falmouth, Cornwall. The SNR was estimated using the GS method for six different land covers and a range of wavelengths. Large differences in the SNR existed between land cover types. It follows that single estimates of SNR (e.g. for one land cover) should not be associated with an image (as a whole). It is recommended that either (i) each statistic is reported per land cover type per wavelength or (ii) that an image of local statistics is reported per wavelength. The regression of noise on signal can be used to separate independent noise (intercept) from signal-dependent noise (slope). Variation in the noise and SNR estimates can be used to (i) allow more accurate prediction of the SNR and (ii) provide information on uncertainty.

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More information

Submitted date: 10 February 2004
Published date: 20 January 2005
Keywords: aerial photography - geography, environmental sciences, remote sensing

Identifiers

Local EPrints ID: 54937
URI: http://eprints.soton.ac.uk/id/eprint/54937
ISSN: 0143-1161
PURE UUID: 8d312cb9-3837-4589-90ba-f41b320065ca
ORCID for P.M. Atkinson: ORCID iD orcid.org/0000-0002-5489-6880

Catalogue record

Date deposited: 01 Aug 2008
Last modified: 16 Mar 2024 02:46

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Contributors

Author: P.M. Atkinson ORCID iD
Author: I.M.J. Sargent
Author: G.M. Foody
Author: J. Williams

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