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571.
Using automated supervised segmentation of multibeam backscatter data to delineate seafloor substrates is a relatively novel technique. Low-frequency multibeam echosounders (MBES), such as the 12-kHz EM120, present particular difficulties since the signal can penetrate several metres into the seafloor, depending on substrate type. We present a case study illustrating how a non-targeted dataset may be used to derive information from multibeam backscatter data regarding distribution of substrate types. The results allow us to assess limitations associated with low frequency MBES where sub-bottom layering is present, and test the accuracy of automated supervised segmentation performed using SonarScope® software. This is done through comparison of predicted and observed substrate from backscatter facies-derived classes and substrate data, reinforced using quantitative statistical analysis based on a confusion matrix. We use sediment samples, video transects and sub-bottom profiles acquired on the Chatham Rise, east of New Zealand. Inferences on the substrate types are made using the Generic Seafloor Acoustic Backscatter (GSAB) model, and the extents of the backscatter classes are delineated by automated supervised segmentation. Correlating substrate data to backscatter classes revealed that backscatter amplitude may correspond to lithologies up to 4 m below the seafloor. Our results emphasise several issues related to substrate characterisation using backscatter classification, primarily because the GSAB model does not only relate to grain size and roughness properties of substrate, but also accounts for other parameters that influence backscatter. Better understanding these limitations allows us to derive first-order interpretations of sediment properties from automated supervised segmentation.  相似文献   
572.
573.
The paper focuses on the photogrammetric investigation of geometric models for different types of optical fisheye constructions (equidistant, equisolid-angle, sterographic and orthographic projection). These models were implemented and thoroughly tested in a spatial resection and a self-calibrating bundle adjustment. For this purpose, fisheye images were taken with a Nikkor 8 mm fisheye lens on a Kodak DSC 14n Pro digital camera in a hemispherical calibration room. Both, the spatial resection and the bundle adjustment resulted in a standard deviation of unit weight of 1/10 pixel with a suitable set of simultaneous calibration parameters introduced into the camera model. The camera-lens combination was treated with all of the four basic models mentioned above. Using the same set of additional lens distortion parameters, the differences between the models can largely be compensated, delivering almost the same precision parameters. The relative object space precision obtained from the bundle adjustment was ca. 1:10 000 of the object dimensions. This value can be considered as a very satisfying result, as fisheye images generally have a lower geometric resolution as a consequence of their large field of view and also have a inferior imaging quality in comparison to most central perspective lenses.  相似文献   
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