A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Fast Unsupervised Seafloor Characterization in Sonar Imagery Using Lacunarity
A new unsupervised approach for characterizing seafloor in side-looking sonar imagery is proposed. The approach is based on lacunarity, which measures the pixel-intensity variation, of through-the-sensor data. No training data are required, no assumptions regarding the statistical distributions of the pixels are made, and the universe of (discrete) seafloor types need not be enumerated or known. It is shown how lacunarity can be computed very quickly using integral-image representations, thereby making real-time seafloor assessments on-board an autonomous underwater vehicle feasible. The promise of the approach is demonstrated on high-resolution synthetic-aperture-sonar imagery of diverse seafloor conditions measured at various geographical sites. Specifically, it is shown how lacunarity can effectively distinguish different seafloor conditions and how this fact can be exploited for target-detection performance prediction in mine-countermeasure operations.
Fast Unsupervised Seafloor Characterization in Sonar Imagery Using Lacunarity
A new unsupervised approach for characterizing seafloor in side-looking sonar imagery is proposed. The approach is based on lacunarity, which measures the pixel-intensity variation, of through-the-sensor data. No training data are required, no assumptions regarding the statistical distributions of the pixels are made, and the universe of (discrete) seafloor types need not be enumerated or known. It is shown how lacunarity can be computed very quickly using integral-image representations, thereby making real-time seafloor assessments on-board an autonomous underwater vehicle feasible. The promise of the approach is demonstrated on high-resolution synthetic-aperture-sonar imagery of diverse seafloor conditions measured at various geographical sites. Specifically, it is shown how lacunarity can effectively distinguish different seafloor conditions and how this fact can be exploited for target-detection performance prediction in mine-countermeasure operations.
Fast Unsupervised Seafloor Characterization in Sonar Imagery Using Lacunarity
Williams, David P (author)
2015
Article (Journal)
English
Local classification TIB:
770/3710/5670
BKL:
38.03
Methoden und Techniken der Geowissenschaften
/
74.41
Luftaufnahmen, Photogrammetrie
Multibeam sonar data processing for seafloor classification
| TIBKAT | 2017
Linear-Swept FM (Chirp) Sonar Seafloor Imaging System
| British Library Online Contents | 1993
Seafloor Classification of Multibeam Sonar Data Using Neural Network Approach
| Online Contents | 2005
Cantor Diffractals and Lacunarity
| British Library Conference Proceedings | 1998
SAS - Challenges in Seafloor Imaging and Mapping With Synthetic Aperture Sonar
| Online Contents | 2011