ELIC-Based Texture Advection and Information Entropy-Based Feature Extraction for the Visualization of Surface Flow Field

Abstract

IBFVS is a classical method for visualizing surface flow field, but the quality of the final image is inadequate to get a fully understanding for the visualized flow field. In order to improve the quality of the result image of IBFVS, this paper presents an enhanced IBFVS method based on short ELIC filtering. We take IBFVS as the basic mechanism of our method, and use ELIC filtering to process the injected background image to increase the contrast of the result image. Furthermore, we use information entropy to extract the most important features with highest information in the flow field. Experiment results show that our method generates a better visualization result than IBFVS and the information entropy-based feature extraction method distinguishes the most valuable part in the flow field.