Title :
Diffuse Prior Monotonic Likelihood Ratio Test for Evaluation of Fused Image Quality Measures
Author :
Wei, Chuanming ; Kaplan, Lance M. ; Burks, Stephen D. ; Blum, Rick S.
Author_Institution :
Electr. & Comput. Eng. Dept., Lehigh Univ., Bethlehem, PA, USA
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.
Keywords :
Monte Carlo methods; image fusion; object detection; Monte Carlo simulations; diffuse prior monotonic likelihood ratio test; fused image quality measures; image fusion; target detection; Anthropometry; Government; Humans; Image fusion; Image quality; Layout; Military computing; Permission; Pixel; Testing; Fused image quality measures (FIQM); hypothesis test; image fusion; monotonic correlation (MC); Algorithms; Computer Simulation; Humans; Image Processing, Computer-Assisted; Monte Carlo Method; Visual Perception;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2010.2060344