Use of plan curvature variations for the identification of ridges and channels on DEM

This paper proposes novel improvements in the traditional algorithms for the identification of ridge and channel (also called ravines) topographic features on raster digital elevation models (DEMs). The overall methodology consists of two main steps: (1) smoothing the DEM by applying a mean filter, and (2) detection of ridge and channel features as cells with positive and negative plan curvature respectively, along with a decline and incline in plan curvature away from the cell in direction orthogonal to the feature axis respectively. The paper demonstrates a simple approach to visualize the multi-scale structure of terrains and utilize it for semi-automated topographic feature identification. Despite its simplicity, the revised algorithm produced markedly superior outputs than a comparatively sophisticated feature extraction algorithm based on conic-section analysis of terrain

From Multiview Image Curves to 3D Drawings

Reconstructing 3D scenes from multiple views has made impressive strides in recent years, chiefly by correlating isolated feature points, intensity patterns, or curvilinear structures. In the general setting - without controlled acquisition, abundant texture, curves and surfaces following specific models or limiting scene complexity - most methods produce unorganized point clouds, meshes, or voxel representations, with some exceptions producing unorganized clouds of 3D curve fragments. Ideally, many applications require structured representations of curves, surfaces and their spatial relationships. This paper presents a step in this direction by formulating an approach that combines 2D image curves into a collection of 3D curves, with topological connectivity between them represented as a 3D graph. This results in a 3D drawing, which is complementary to surface representations in the same sense as a 3D scaffold complements a tent taut over it. We evaluate our results against truth on synthetic and real datasets.Comment: Expanded ECCV 2016 version with tweaked figures and including an overview of the supplementary material available at multiview-3d-drawing.sourceforge.ne

The Radio Light Curve of the Gamma-Ray Nova in V407 Cyg: Thermal Emission from the Ionized Symbiotic Envelope, Devoured from Within by the Nova Blast

We present multi-frequency radio observations of the 2010 nova event in the symbiotic binary V407 Cygni, obtained with the Karl G. Jansky Very Large Array and spanning 1-45 GHz and 17-770 days following discovery. This nova---the first ever detected in gamma rays---shows a radio light curve dominated by the wind of the Mira giant companion, rather than the nova ejecta themselves. The radio luminosity grew as the wind became increasingly ionized by the nova outburst, and faded as the wind was violently heated from within by the nova shock. This study marks the first time that this physical mechanism has been shown to dominate the radio light curve of an astrophysical transient. We do not observe a thermal signature from the nova ejecta or synchrotron emission from the shock, due to the fact that these components were hidden behind the absorbing screen of the Mira wind. We estimate a mass loss rate for the Mira wind of Mdot_w ~ 10^-6 M_sun/yr. We also present the only radio detection of V407 Cyg before the 2010 nova, gleaned from unpublished 1993 archival VLA data, which shows that the radio luminosity of the Mira wind varies by a factor of >~20 even in quiescence. Although V407 Cyg likely hosts a massive accreting white dwarf, making it a candidate progenitor system for a Type Ia supernova, the dense and radially continuous circumbinary material surrounding V407 Cyg is inconsistent with observational constraints on the environments of most Type Ia supernovae.Comment: Resubmitted to ApJ after incorporating referee's comment