Representation of colored images by manifolds embedded in higher dimensional non-Euclidean space

Nir Sochen, Yehoshua Y. Zeevi

Research output: Contribution to conferencePaperpeer-review

Abstract

In image analysis, processing and understanding, it is highly desirable to process the image and feature domains by methods that are specific to these domains. We show how the geometrical framework for scale-space flows is most convenient for this purpose, and demonstrate, as an example, how one can switch continuously between different processing flows of images and color domains. The parameter that interpolates between the norms is the luminance strength, taken here as a local function of the image embedding space. The resulting spatial and/or luminance preserving flow can be used for conditional denoising, enhancement and segmentation. This example demonstrates that the proposed framework can incorporate context or task dependent data, furnished by either the human user or by an active vision subsystem, in a coherent and convenient way.

Original languageEnglish
Pages166-170
Number of pages5
StatePublished - 1998
Externally publishedYes
EventProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3) - Chicago, IL, USA
Duration: 4 Oct 19987 Oct 1998

Conference

ConferenceProceedings of the 1998 International Conference on Image Processing, ICIP. Part 2 (of 3)
CityChicago, IL, USA
Period4/10/987/10/98

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