title: An early underwater artificial vision model in ocean investigations via independent component analysis.
abstract: Underwater vision is one of the dominant senses and has shown great prospects in ocean investigations. In this paper, a hierarchical Independent Component Analysis (ICA) framework has been established to explore and understand the functional roles of the higher order statistical structures towards the visual stimulus in the underwater artificial vision system. The model is inspired by characteristics such as the modality, the redundancy reduction, the sparseness and the independence in the early human vision system, which seems to respectively capture the Gabor-like basis functions, the shape contours or the complicated textures in the multiple layer implementations. The simulation results have shown good performance in the effectiveness and the consistence of the approach proposed for the underwater images collected by autonomous underwater vehicles (AUVs).
authors.affiliation: School of Information Science and Engineering, Ocean University of China, Qingdao 266100, China. nianrui_80@163.com
authors.forename: Rui
authors.initials: R
authors.lastname: Nian
authors.forename: Fang
authors.initials: F
authors.lastname: Liu
authors.forename: Bo
authors.initials: B
authors.lastname: He
mesh_terms: D001185:Artificial Intelligence; D032701:Biomimetics / Q000379:methods*; D003198:Computer Simulation; D007101:Immersion; D008959:Models, Neurological; D009792:Oceans and Seas; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D012371:Robotics / Q000379:methods*; D014796:Visual Perception