Images as embedding maps and minimal surfaces: A unified approach for image diffusion

R. Kimmel; R. Malladi; N. Sochen

Images as embedding maps and minimal surfaces: A unified approach for image diffusion

R. Kimmel^*
, R. Malladi
, N. Sochen

^*Corresponding author for this work

Lawrence Berkeley National Laboratory

Research output: Contribution to conference › Paper › peer-review

Abstract

We introduce a new geometrical framework for image processing. This framework finds a seamless link between the TV-L₁ and the L₂ norms that are often used in image processing, based on the geometry of the image and its interpretation as a surface. It unifies most of the current `scale space' models for images by a simple selection of one parameter, yet more important, it enables to introduce new methods to deal with images in a simple and natural way. A functional called `Polyakov action', borrowed from high energy physics, is shown to be useful for image enhancement in color, texture, volumetric medical, data, movies, and more.

Original language	English
Pages	368-371
Number of pages	4
State	Published - 1997
Externally published	Yes
Event	Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3) - Santa Barbara, CA, USA Duration: 26 Oct 1997 → 29 Oct 1997

Conference

Conference	Proceedings of the 1997 International Conference on Image Processing. Part 2 (of 3)
City	Santa Barbara, CA, USA
Period	26/10/97 → 29/10/97

Cite this

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AU - Malladi, R.

AU - Sochen, N.

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Images as embedding maps and minimal surfaces: A unified approach for image diffusion

Abstract

Conference

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