Active-passive data fusion algorithms for seafloor imaging and classification from CZMIL data

Joong Yong Park; Vinod Ramnath; Viktor Feygels; Minsu Kim; Abhinav Mathur; Jennifer Aitken; Grady Tuell

doi:10.1117/12.851991

12 May 2010 Active-passive data fusion algorithms for seafloor imaging and classification from CZMIL data

Joong Yong Park, Vinod Ramnath, Viktor Feygels, Minsu Kim, Abhinav Mathur, Jennifer Aitken, Grady Tuell

Proceedings Volume 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI; 769515 (2010) https://doi.org/10.1117/12.851991
Event: SPIE Defense, Security, and Sensing, 2010, Orlando, Florida, United States

Abstract

CZMIL will simultaneously acquire lidar and passive spectral data. These data will be fused to produce enhanced seafloor reflectance images from each sensor, and combined at a higher level to achieve seafloor classification. In the DPS software, the lidar data will first be processed to solve for depth, attenuation, and reflectance. The depth measurements will then be used to constrain the spectral optimization of the passive spectral data, and the resulting water column estimates will be used recursively to improve the estimates of seafloor reflectance from the lidar. Finally, the resulting seafloor reflectance cube will be combined with texture metrics estimated from the seafloor topography to produce classifications of the seafloor.

Citation Download Citation

Joong Yong Park, Vinod Ramnath, Viktor Feygels, Minsu Kim, Abhinav Mathur, Jennifer Aitken, and Grady Tuell "Active-passive data fusion algorithms for seafloor imaging and classification from CZMIL data", Proc. SPIE 7695, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVI, 769515 (12 May 2010); https://doi.org/10.1117/12.851991

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