A Good Image Model Eases Restoration

Abstract

What we believe images are determines how we take actions in image and lowlevel vision analysis. In the Bayesian framework, it is known as the importance of a good image prior model. This paper intends to give a concise overview on the vision foundation, mathematical theory, computational algorithms, and various classical as well as unexpected new applications of the BV (bounded variation) image model, first introduced into image processing by Rudin, Osher, and Fatemi in 1992 Physica D, 60:259-268.

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Document Details

Document Type
Technical Report
Publication Date
Feb 06, 2002
Accession Number
ADA437474

Entities

People

  • Jianhong Shen
  • Tony F. Chan

Organizations

  • University of California, Los Angeles

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Applied Mathematics
  • Bayesian Networks
  • Computational Science
  • Computer Graphics
  • Computer Vision
  • Differential Equations
  • Digital Images
  • Equations
  • Geometry
  • Image Processing
  • Image Restoration
  • Mathematical Analysis
  • Mathematical Models
  • Mathematics
  • Models
  • Packet Loss

Readers

  • Computer Vision.
  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms