On the use of Hough transform for context-based image compression in hybrid raster/vector 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 contextbased compression of the raster image. In both techniques, Hough transform is used for extracting the line features from the raster image. The first technique utilizes the line features to improve the prediction accuracy in the context modeling. The second 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. In both cases, we achieve better compression performance.