Establishing an objective basis for image compositing in satellite oceanography

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Breaker, L. C., Armstrong, E. M., & Endris, C. A. (2010). Establishing an objective basis for image compositing in satellite oceanography. Remote Sensing of Environment, 114(2), 345-362. doi:10.1016/j.rse.2009.09.014
TitleEstablishing an objective basis for image compositing in satellite oceanography
AuthorsL. Breaker, E. Armstrong, C. Endris
AbstractThis study strives to establish an objective basis for image compositing in satellite oceanography. Image compositing is a powerful technique for cloud filtering that often emphasizes cloud clearing at the expense of obtaining synoptic coverage. Although incomplete cloud removal in image compositing is readily apparent, the loss of synopticity, often, is not. Consequently, the primary goal of image compositing should be to obtain the greatest amount of cloud-free coverage or clarity in a period short enough that synopticity, to a significant degree, is preserved. To illustrate the process of image compositing and the problems associated with it, we selected a region off the coast of California and constructed two 16-day image composites, one, during the spring, and the second, during the summer of 2006, using Advanced Very High Resolution Radiometer (AVHRR) InfraRed (IR) satellite imagery. Based on the results of cloud clearing for these two 16-day sequences, rapid cloud clearing occurred up to day 4 or 5, followed by much slower cloud clearing out to day 16, suggesting an explicit basis for the growth in cloud clearing. By day 16, the cloud clearing had, in most cases, exceeded 95%. Based on these results, a shorter compositing period could have been employed without a significant loss in clarity. A method for establishing an objective basis for selecting the period for image compositing is illustrated using observed data. The loss in synopticity, which, in principle, could be estimated from pattern correlations between the images in the composite, was estimated from a separate time series of SST since the loss of synopticity, in our approach, is only a function of time. The autocorrelation function of the detrended residuals provided the decorrelation time scale and the basis for the decay process, which, together, define the loss of synopticity. The results show that (1) the loss of synopticity and the gain in clarity are inversely related, (2) an objective basis for selecting a compositing period corresponds to the day number where the decay and growth curves for synopticity and clarity intersect, and (3), in this case, the point of intersection occurred 3.2 days into the compositing period. By applying simple mathematics it was shown that the intersection time for the loss in synopticity and the growth in clarity is directly proportional to the initial conditions required to specify the clarity at the beginning of the compositing period, and inversely proportional to the sum of the rates of growth for clarity and the loss in synopticity. Finally, we consider these results to be preliminary in nature, and, as a result, hope that future work will bring forth significant improvements in the approach outlined in this study. © 2009 Elsevier Inc. All rights reserved.
JournalRemote Sensing of Environment
Start page345
End page362
SubjectsAutocorrelation functions, California, Cloud clearings, Cloud removal, Compositing, Decay process, Decorrelations, Function of time, Growth curves, Image composites, Image compositing, Initial conditions, Observed data, Pattern correlation, Satellite oceanography, Synopticity, Time-scales, Coastal zones, Oceanography, Regression analysis, Time series, Satellite imagery, AVHRR, correlation, image analysis, infrared imagery, inverse analysis, pattern recognition
NoteCited By (since 1996):3, Oceanography, CODEN: RSEEA