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- W2029231714 abstract "Ratio-based bottom depth-retrieval algorithms are conceptually simple relative to other algorithms and can be effective. The objective of this study was to determine the utility of imposing a spatial-smoothing assumption on three ratio-based, feed-forward remote-sensing bathymetry algorithms: Polcyn et al., Stumpf et al., and Dierssen et al. We consider three smoothing operators: median, Savitzky-Golay, and linear diffusion with data fidelity, applied in three domains: spatial, spectral, and spectral-spatial. Thus, we consider nine smoothing methods. In addition, we consider two points at which smoothing is applied: one before the inversion process (pre-smoothing) and the other after the inversion process (post-smoothing). Our new formulations were tested with synthetic data, in situ remote-sensing reflectance, and simultaneous acoustic bathymetry, acquired in optically shallow waters. Analysis and results from the synthetic-data experiment indicate that pre-smoothing method is more effective than post-smoothing method. The field-data experiments indicate that spatial-domain smoothing is effective regardless of the type of smoothing operator, whereas spectral smoothing is not. Spectral-spatial-domain smoothing is as effective as spatial-domain smoothing, but is prone to over-segmentation. Effectiveness of spatial pre-smoothing was observed with every ratio-based inversion method, which suggests potential universal applicability of smoothing operators to ratio-based algorithms." @default.
- W2029231714 created "2016-06-24" @default.
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- W2029231714 date "2009-08-01" @default.
- W2029231714 modified "2023-09-26" @default.
- W2029231714 title "Conditioning of reflectance signals by linear diffusion for improving narrow-band ratio-based remote-sensing bottom depth retrieval in shallow coastal waters" @default.
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- W2029231714 doi "https://doi.org/10.1117/1.3211116" @default.
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