Visualizing 2D Flows with Animated Arrow Plots

Flow fields are often represented by a set of static arrows to illustrate scientific vulgarization, documentary film, meteorology, etc. This simple schematic representation lets an observer intuitively interpret the main properties of a flow: its orientation and velocity magnitude. We propose to generate dynamic versions of such representations for 2D unsteady flow fields. Our algorithm smoothly animates arrows along the flow while controlling their density in the domain over time. Several strategies have been combined to lower the unavoidable popping artifacts arising when arrows appear and disappear and to achieve visually pleasing animations. Disturbing arrow rotations in low velocity regions are also handled by continuously morphing arrow glyphs to semi-transparent discs. To substantiate our method, we provide results for synthetic and real velocity field datasets

Horizontal flow fields observed in Hinode G-band images. I. Methods

Context: The interaction of plasma motions and magnetic fields is an important mechanism, which drives solar activity in all its facets. For example, photospheric flows are responsible for the advection of magnetic flux, the redistribution of flux during the decay of sunspots, and the built-up of magnetic shear in flaring active regions. Aims: Systematic studies based on G-band data from the Japanese Hinode mission provide the means to gather statistical properties of horizontal flow fields. This facilitates comparative studies of solar features, e.g., G-band bright points, magnetic knots, pores, and sunspots at various stages of evolution and in distinct magnetic environments, thus, enhancing our understanding of the dynamic Sun. Methods: We adapted Local Correlation Tracking (LCT) to measure horizontal flow fields based on G-band images obtained with the Solar Optical Telescope on board Hinode. In total about 200 time-series with a duration between 1-16 h and a cadence between 15-90 s were analyzed. Selecting both a high-cadence (dt = 15 s) and a long-duration (dT = 16 h) time-series enabled us to optimize and validate the LCT input parameters, hence, ensuring a robust, reliable, uniform, and accurate processing of a huge data volume. Results: The LCT algorithm produces best results for G-band images having a cadence of 60-90 s. If the cadence is lower, the velocity of slowly moving features will not be reliably detected. If the cadence is higher, the scene on the Sun will have evolved too much to bear any resemblance with the earlier situation. Consequently, in both instances horizontal proper motions are underestimated. The most reliable and yet detailed flow maps are produced using a Gaussian kernel with a size of 2560 km x 2560 km and a full-width-at-half-maximum (FWHM) of 1200 km (corresponding to the size of a typical granule) as sampling window.Comment: 12 pages, 8 figures, 4 tables, accepted for publication in Astronomy and Astrophysic

An image-based approach to interactive crease extraction and rendering

AbstractRidge and valley manifolds are receiving a growing attention in visualization research due to their ability to reveal the shapes of salient structures in numerical datasets across scientific, engineering, and medical applications. However, the methods proposed to date for their extraction in the visualization and image analysis literature are computationally expensive and typically applied in an offline setting. This setup does not properly support a userdriven exploration, which often requires control over various parameters tuned to filter false positives and spurious artifacts and highlight the most significant structures. This paper presents a GPU-based adaptive technique for crease extraction and visualization across scales. Our method combines a scale-space analysis of the data in pre-processing with a ray casting approach supporting a robust and efficient one-dimensional numerical search, and an image-based rendering strategy. This general framework achieves high-quality crease surface representations at interactive frame rates. Results are proposed for analytical, medical, and computational datasets