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Modern visualization methods are needed to cope with very high-dimensional data. Efficient visual analytical techniques are required to extract the information content in these data. The large number of possible projections for each method, which usually grow quadrat-ically or even exponentially with the number of dimensions, urges the necessity to employ(More)
Parallel coordinates and scatterplot matrices are widely used to visualize multi-dimensional data sets. But these visualization techniques are insufficient when the number of dimensions grows. To solve this problem, different approaches to pre-select the best views or dimensions have been proposed in the last years. However, there are still several(More)
The scatterplot matrix (SPLOM) is a well-established technique to visually explore high-dimensional data sets. It is characterized by the number of scatterplots (plots) of which it consists of. Unfortunately, this number quadrat-ically grows with the number of the data set's dimensions. Thus, a SPLOM scales very poorly. Consequently, the usefulness of(More)
The concept of continuous scatterplot (CSP) is a modern visualization technique. The idea is to define a scalar density value based on the map between an n-dimensional spatial domain and an m-dimensional data domain, which describe the CSP space. Usually the data domain is two-dimensional to visually convey the underlying, density coded, data. In this paper(More)
Two-dimensional transfer functions are an effective and well-accepted tool in volume classification. The design of them mostly depends on the user's experience and thus remains a challenge. Therefore, we present an approach in this paper to automate the transfer function design based on 2D density plots. By exploiting their smoothness, we adopted the Morse(More)
Continuous Parallel Coordinates (CPC) are a contemporary visualization technique in order to combine several scalar fields, given over a common domain. They facilitate a continuous view for parallel coordinates by considering a smooth scalar field instead of a finite number of straight lines. We show that there are feature curves in CPC which appear to be(More)
Erläuterungen anhand anschaulicher Beispiele verdeut-licht und so für den Leser nachvollziehbar. Abstract Concerning multi-dimensional data sets there exist a lot of visual-based as well as automatical techniques to detect inherent relations and characteristics. Due to the (increasing) size and complexity of such data, it is necessary to combine both(More)