A Locally-Adaptive Metric for Contrast-Fusion of Noisy Multimodal Imagery

Abstract

We propose a new technique for reducing the effect of noise on contrast fusion of multimodal imagery, yielding higher quality results than can be obtained with previous methods. We rely on local non-parametric estimation of band gradient entropies as a relative measure of geometric structure. This work builds upon previous work by the author, and is exemplified with remote sensing applications. Quantitative measures of performance are given on ground-truth data, which indicate the advantages of the new technique over existing approaches.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2000
Accession Number
ADA453160

Entities

People

  • Diego A. Socolinsky

Tags

Communities of Interest

  • Sensors

DTIC Thesaurus Topics

  • Algorithms
  • Change Detection
  • Climate Change
  • Computations
  • Contrast
  • Coordinate Systems
  • Detectors
  • Frequency Domain
  • Gaussian Noise
  • Magnetic Resonance
  • New York
  • Noise
  • Perception
  • Probability
  • Random Variables
  • Remote Sensing
  • Standards

Readers

  • Computer Vision.
  • Systems Analysis and Design