Hrvatska znanstvena Sekcija img
3 gif
 About the project
4 gif
Basic search
Advanced search
Statistical data
Other bibliographies
Similar projects
 Catalogues and databases

Bibliographic record number: 369658


Authors: Galić, Irena; Weickert, Joachim; Welk, Martin; Bruhn, Andrés; Belyaev, Alexander; Seidel, Hans-Peter
Title: Image Compression with Anisotropic Diffusion
Source: Journal of mathematical imaging and vision (0924-9907) 31 (2008), 2-3; 255-269
Paper type: article
Keywords: partial differential equations; nonlinear diffusion; image compression; image inpainting
Compression is an important field of digital image processing where well-engineered methods with high performance exist. Partial differential equations (PDEs), however, have not much been explored in this context so far. In our paper we introduce a novel framework for image compression that makes use of the interpolation qualities of edge-enhancing diffusion. Although this anisotropic diffusion equation with a diffusion tensor was originally proposed for image denoising, we show that it outperforms many other PDEs when sparse scattered data must be interpolated. To exploit this property for image compression, we consider an adaptive triangulation method for removing less significant pixels from the image. The remaining points serve as scattered interpolation data for the diffusion process. They can be coded in a compact way that reflects the B-tree structure of the triangulation. We supplement the coding step with a number of amendments such as error threshold adaptation, diffusion-based point selection, and specific quantisation strategies. Our experiments illustrate the usefulness of each of these modifications. They demonstrate that for high compression rates, our PDE-based approach does not only give far better results than the widelyused JPEG standard, but can even come close to the quality of the highly optimised JPEG2000 codec.
Project / theme: 165-0362980-2002
Original language: ENG
Citation databases: Current Contents Connect (CCC)
Science Citation Index Expanded (SCI-EXP) (sastavni dio Web of Science Core Collectiona)
Category: Znanstveni
Research fields:
Computer science
Broj citata:
DOI: 10.1007/s10851-008-0087-0
URL cjelovitog rada:
Google Scholar: Image Compression with Anisotropic Diffusion
Contrib. to CROSBI by: (, 28. Lis. 2008. u 12:05 sati

  Print version   za tiskati