Vector field visualization: analysis of feature extraction methods

This paper addresses the problem of the visualization of vector-valued images. Attempting to synthesize a display matched to the capabilities of a human observer, we have reduced the problem to the extraction of the best linear feature of the vector field. In previous work, we have proposed and demonstrated several new nonparametric feature extraction criteria (projection indices) that make use of both the spatial and multivariate structures of the data. We present a theoretical analysis of these projection indices and a Monte-Carlo study of their effectiveness. The study uses performance measures derived from a decision-theoretic model of the human observer