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Bibliographic record number: 369664

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Authors: Galić, Irena; Weickert, Joachim; Welk, Martin; Bruhn, Andrés; Belyaev, Alexander; Seidel, Hans-Peter
Title: Image Compression with Anisotropic Diffusion
( Image Compression with Anisotropic Diffusion )
Source: Technical Report No. 203, Department of Mathematics, Saarland University, Saarbrücken, Germany
Type: Technical Report
Year: 2008
Keywords: partial differential equations; nonlinear diffusion; image compression; image inpainting
( partial differential equations; nonlinear diffusion; image compression; image inpainting )
Abstract:
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.
Original language: eng
Research fields:
Computer science
Contrib. to CROSBI by: irena@etfos.hr (irena@etfos.hr), 28. Lis. 2008. u 12:12 sati



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