Diffuse Prior Monotonic Likelihood Ratio Test for Evaluation of Fused Image Quality Measures

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 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 method computes a new diffuse prior monotonic likelihood ratio (DPMLR) to facilitate the comparison of the H1 hypothesis that the intrinsic human detection performance is related to the FIQM via a monotonic function against 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 with test cases considering over 35 scenes and various image fusion algorithms.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2011
Accession Number
ADA559291

Entities

People

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

Organizations

  • Lehigh University

Tags

Communities of Interest

  • Biomedical
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Contrast
  • Detection
  • Dynamic Range
  • Electronic Mail
  • Image Processing
  • Image Segmentation
  • Integrals
  • Long-Wavelength Infrared Radiation
  • Military Operations
  • Military Research
  • Motor Skills
  • Perception
  • Probability
  • Sequences
  • Simulations
  • Statistics

Readers

  • Image Processing and Computer Vision.
  • Organizational Psychology.
  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.