Using Hough transform for context-based image compression in hybrid rasterÕvector applications

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. © 2002 SPIE and IS&T. [DOI: 10.1117/1.1455014]