A1 Journal article (refereed), original research

Using Hough Transform for Context-based Image Compression in Hybrid Raster/Vector Applications


LUT Authors / Editors

Publication Details
Authors: Fränti Pasi, Ageenko Eugene, Kukkonen Saku, Kälviäinen Heikki
Publication year: 2002
Language: English
Related Journal or Series Information: Journal of Electronic Imaging
Volume number: 11
Issue number: 2
JUFO-Level of this publication:
Open Access: Not an Open Access publication

Abstract
In a hybrid raster/vector system, two representations of the image are stored. Digitized raster image preserves the original drawing in its exact visual form, whereas additional vector data can be used for resolution-independent reproduction, image editing, analysis, and indexing operations. We introduce two techniques for utilizing the vector features in context-based compression of the raster image. In both techniques, Hough transform is used for extracting the line features from the raster image. The first technique uses a feature-based filter for removing noise near the borders of the extracted line elements. This improves the image quality and results in more compressible raster image. The second technique utilizes the line features to improve the prediction accuracy in the context modeling. In both cases, we achieve better compression performance.

Last updated on 2017-22-03 at 15:06