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