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The speed of the turbidity estimation method was 200 sampling points/second.
N = 100 random sampling points were taken for each turbidity estimation.
In this section, we evaluated the turbidity estimation approach and the aerial perspective rendering model.
Simulations showed that uncertainty for turbidity estimation associated with different particle types and bidirectional effects is typically less than 6%.
The real scenes of the experiments correspond to the scenes captured for the turbidity estimation test seen in Fig. 8.
We tested our approach for turbidity estimation using static omnidirectional images of both simulated skies and captured skies.
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Our conclusions from the analysis are that the Secchi depth estimation works very well, while the turbidity estimates are a bit more scattered.
The mixture became turbid but turbidity disappeared during gentle stirring.
Particular emphasis was given to the third investigation into the use of satellite remote sensing techniques for estimation of the turbidity level in the BRE.
Yet previous estimations of reservoir turbidity currents are mostly based on simple empirical relations and it remains unclear how and to what extent physically based numerical models can resolve current evolution as compared against field observations.
Lags with statistically significant slope estimates for turbidity were identified.
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