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

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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.

Document Type: Research Article


Affiliations: 1: School of Geography, University of Southampton, Highfield, Southampton SO17 1BJ, UK 2: Ordnance Survey, Romsey Road, Maybush, Southampton SO16 4GU, UK 3: QinetiQ, St Andrews Road, Malvern, Worcestershire WR14 3PS, UK

Publication date: 2005-11-20

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