Diffuse Prior Monotonic Likelihood Ration Test for Evaluation of Fused Image Quality Metrics

Abstract

This paper introduces a novel method to score how well proposed fused image quality measures (FIQMs) indicate the effectiveness of humans to detect targets of interest in fused imagery. The human detection performance is measured via human perception experiments. A good FIQM should relate to perception results in a monotonic fashion. The new method, the diffuse prior monotonic likelihood ratio (DPMLR) test compares the H1 hypothesis that the intrinsic human detection performance is related to the FIQM via a monotonic function to the null hypothesis that the detection and image quality relationship is random. The paper discusses many interesting properties of the DPMLR and demonstrates the effectiveness of the DPMLR test via Monte Carlo Simulations. Finally, the DPMLR is used to score FIQMs over 35 scenes implementing various image fusion algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 2009
Accession Number
ADA533363

Entities

People

  • Chuanming Wei
  • Lance Kaplan
  • Rick Blum
  • Stephen D. Burks

Organizations

  • United States Army Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Contrast
  • Data Science
  • Detection
  • False Alarms
  • Governments
  • Hypotheses
  • Information Science
  • Long-Wavelength Infrared Radiation
  • Military Research
  • Motor Skills
  • Observation
  • Observers
  • Perception
  • Power Series
  • Simulations
  • Test And Evaluation

Readers

  • Computer Vision.
  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.
  • Regression Analysis.