@article{fdi:010078155,
  title = {{E}rror proxies in video-based depth inversion : temporal celerity estimation},
  author = {{A}bessolo, {G}. {O}. and {A}lmar, {R}afa{\¨e}l and {B}onou, {F}. and {B}ergsma, {E}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he accuracy of bathymetric measurements is crucial, especially to understand coastal processes. {V}ideo-based depth inversion methods have been widely developed in recent years, but they remain noisy, with typical errors due to the breakpoint optical and non-linear effects. {A}mong the spectral and temporal approaches to video depth inversion, only the spectral approach applies an error criterion to identify erroneous data. {H}ere, two error proxies are assimilated for the first time in the temporal approach, using a {K}alman filter applied to 3.5 years ({F}ebruary 2013 to {S}eptember 2016) of video images. {D}ifferences between filtered and unfiltered bathymetries were observed to be correlated with the proxies considered. {A} validation with field data on a 10-day experiment is performed between the original bathymetries and the filtered bathymetries. {T}he results indicate that the mean square error can be reduced by at least 30%. {B}oth proxies show good ability to correct depth estimates. {A}lthough the results are promising, validation of these approximations must be performed under various hydrodynamic and atmospheric conditions.},
  keywords = {{B}athymetry ; video imagery ; nearshore ; error proxy},
  booktitle = {},
  journal = {{J}ournal of {C}oastal {R}esearch},
  numero = {{N}o sp{\'e}cial 95},
  pages = {1101--1105},
  ISSN = {0749-0208},
  year = {2020},
  DOI = {10.2112/si95-214.1},
  URL = {https://www.documentation.ird.fr/hor/fdi:010078155},
}