A general framework for low level vision

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A general framework for low level vision (1998)

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by Nir Sochen , Ron Kimmel , Ravikanth Malladi

Venue:	IEEE TRANS. ON IMAGE PROCESSING
Citations:	215 - 36 self

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@ARTICLE{Sochen98ageneral,
    author = {Nir Sochen and Ron Kimmel and Ravikanth Malladi},
    title = {A general framework for low level vision},
    journal = {IEEE TRANS. ON IMAGE PROCESSING},
    year = {1998},
    pages = {310--318}
}

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Abstract

We introduce a new geometrical framework based on which natural flows for image scale space and enhancement are presented. We consider intensity images as surfaces in the space. The image is, thereby, a two-dimensional (2-D) surface in three-dimensional (3-D) space for gray-level images, and 2-D surfaces in five dimensions for color images. The new formulation unifies many classical schemes and algorithms via a simple scaling of the intensity contrast, and results in new and efficient schemes. Extensions to multidimensional signals become natural and lead to powerful denoising and scale space algorithms.

Keyphrases

low level vision geometrical framework natural flow image enhancement image smoothing powerful denoising 2-d surface intensity image efficient scheme simple scaling index term color image processing nonlinear image diffusion color image gray-level image image scale space new geometrical framework multidimensional signal scale space algorithm intensity contrast

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