Super Resolution: An Overview

Abstract

Super-resolution algorithms produce a single high-resolution image from a set of several, low-resolution images of the desired scene. The low-resolution frames are shifted differently with respect to the high resolution frame with subpixel increments. This paper presents first a theoretical overview of super-resolution algorithms. The most important methods, namely, the iterative back-projection, projection onto convex sets, and maximum a posteriori estimation are then compared within the same framework of implementation.

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Document Details

Document Type
Technical Report
Publication Date
Jul 25, 2005
Accession Number
ADA449806

Entities

People

  • C. Papathanassiou
  • M. Petrou

Organizations

  • University of Surrey

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Engineered Resilient Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Algorithms
  • Bayes Theorem
  • Coordinate Systems
  • Errors
  • Frequency Domain
  • Grids
  • High Resolution
  • Interpolation
  • Iterations
  • Low Resolution
  • Noise
  • Observation
  • Physical Sciences
  • Probability
  • Probability Density Functions
  • Remote Sensing

Readers

  • Image Processing and Computer Vision.
  • Mathematical Modeling and Probability Theory.