No abstract

Abstract. In this paper, we propose a new model for image restoration and image decomposition into cartoon and texture, based on the total variation minimization of Rudin, Osher, and Fatemi [Phys. D, 60 (1992)

Two complementary geometric structures for the topographic representation of an image are developed in this work. The first one computes a description of the Morse-topological structure of the image, while the second one computes a simplified version of its drainage structure. The topographic significance of the Morse and drainage structures of digital elevation maps (DEMs) suggests that they can been used as the basis of an efficient encoding scheme. As an application, we combine this geometric representation with an interpolation algorithm and lossless data compression schemes to develop a compression scheme for DEMs. This algorithm achieves high compression while controlling the maximum error in the decoded elevation map, a property that is necessary for the majority of applications dealing with DEMs. We present the underlying theory and compression results for standard DEM data.

No abstract

Ridge and valley structures are important image features, especially in oriented textures. Usually, the extraction of these structures requires a prefiltering step to regularize the source image. In this paper, we show that classical diffusion-based filters are not always appropriate for this task and propose a new filtering process. This new filter can be interpreted as an example of introducing the intrinsic image structure in a diffusion process. c 2001 Elsevier Science (USA)