Highlighting pipelines offshore Norway: visualization and quantitative analysis

Sonar profiler data of the seabottom are 3D data sets that can cover huge survey areas with many gaps. This paper describes a multiresolution visualization framework that is being optimized for dealing with such data taking into account both the CPU time and the user interactivity. The paper describes the techniques employed: (a) the construction of a quadtree that allows to eliminate gaps by interpolating available 3D data, (b) a first but coarse visualization at a high tree level in order to rapidly change or adjust the ROI, and (c) a very efficient triangulation (mesh reduction) that allows for a fast interactivity even at the highest detail level. By using one single octree all this processing can be combined because (1) gaps can be filled by interpolation because they are smaller at higher tree levels, (2) connected components can be projected down the tree and refined using the data available there and (3) triangulations at higher tree levels can be used to steer those at lower levels to fill efficiently large and smooth surface areas. As a result, huge data sets can be visualized in near realtime with OpenGL/VRML using shading instead of wireframes, and this enables a fast searching for objects in the seabottom. Real CPU times are presented for the visualization of a real sonar data set which was obtained in the North Sea, offshore Norway. These data are visualized at a low resolution, showing the overall shape of the seabottom, and at a high resolution, showing a (semi-)buried pipeline. In order to detect an object at such a high resolution additional techniques are applied to the data: (a) an interslice interpolation in order to cope with the increased data sparseness and (b) a maximum-homogeneity filtering in order to cope with the decreased SNR. After the extraction of the pipeline a thinning technique is applied in order to be able to quantify its length