Ill-Posed Problems and Regularization Analysis in Early Vision,

Abstract

One of the best definitions of early vision is that it is inverse optics-a set of computational problems that both machines and biological organisms have to solve. While in classical optics the problem is to determine the images of physical objects, vision is confronted with the inverse problem of recovering three-dimensional shape from the light distribution in the image. Most processes of early vision such as stereomatching, computation of motion and all the 'structure from' processes can be regarded as solutions to inverse problems. This common characteristic of early vision can be formalized: most early vision problems are 'ill-posed problems' in the sense of Hadamard. It is shown that a mathematical theory developed for regularizing ill-posed problems lease in a natural way to the solution of early vision problems in terms of variational principles of a certain class. This is a new theoretical framework for some of the variational solutions already obtained in the analysis of early vision processes. It also shows how several other problems in early vision can be approached and solved. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1984
Accession Number
ADA147753

Entities

People

  • T. Poggio
  • V. Torre

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Change Detection
  • Computational Science
  • Computer Graphics
  • Computer Science
  • Computer Vision
  • Detection
  • Differential Equations
  • Electrical Engineering
  • Equations
  • Image Processing
  • Information Processing
  • Inverse Problems
  • Pattern Recognition
  • Stratified Fluids
  • Two Dimensional
  • Variational Principles

Readers

  • Educational Psychology
  • Neural Network Machine Learning.
  • Theoretical Analysis.