Open AccessVisual glare limits of HDR displays in medical imaging
Author(s) -
Rizzi Alessandro,
Barricelli Barbara Rita,
Bonanomi Cristian,
Albani Luigi,
Gianini Gabriele
Publication year - 2018
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2018.5252
Subject(s) - luminance , high dynamic range , computer science , computer vision , glare , high dynamic range imaging , human visual system model , limiting , artificial intelligence , medical imaging , dynamic range , display device , set (abstract data type) , image (mathematics) , engineering , materials science , layer (electronics) , composite material , programming language , operating system , mechanical engineering
Emerging display technologies are proposing monitors for medical imaging with an extended dynamic range of luminance. Those devices offer the opportunity to extend the range of visual information displayed, but the limits of the human visual system (HVS) in perceiving such information can cancel the advantages. To investigate this problem, we present a set of experiments, to assess the visual response of the HVS to controlled high dynamic range (HDR) content. They analyse the effects of glare. Using a typical HDR display, tailored for medical imaging applications, they first study the dependence of the visible dynamic range from the inter‐ocular glare, induced by different backgrounds, then the effect of glare on the detection of test elements on medical radiographic images. Finally, they assess the influence of luminance‐equivalent backgrounds with different structure in the detection of test patches. The results of the experiments confirm the glare as a major player in influencing visual information detection. Glare has a significant impact in limiting the amount of visual information actually perceived, consequently limiting analysis capabilities of such images. This confirms the importance of investigating and considering the characteristics of human vision in the design and test of HDR imaging systems.