Paper
16 October 2013 Defining human contrast sensitivity and discrimination from complex imagery
S. Triantaphillidou, J. Jarvis, G. Gupta, H. Rana
Author Affiliations +
Abstract
Shape, form and detail define image structure in our visual world. These attributes are dictated primarily by local variations in luminance contrast. Defining human contrast sensitivity (threshold of contrast perception) and contrast discrimination (ability to differentiate between variations in contrast) directly from real complex scenes is of outermost relevance to our understanding of spatial vision. The design and evaluation of imaging equipment, used in both field operations and security applications, require a full description of strengths and limitations of human spatial vision. This paper is concerned with the measurement of the following four human contrast sensitivity functions directly from images of complex scenes: i) Isolated Contrast Sensitivity (detection) Function (iCSF); ii) Contextual Contrast Sensitivity (detection) Function (cCSF); iii) Isolated Visual Perception (discrimination) Function (iVPF) and iv) Contextual Visual Perception (discrimination) Function (cVPF). The paper also discusses the following areas: Barten’s mathematical framework for modeling contrast sensitivity and discrimination; spatial decomposition of image stimuli to a number of spatial frequency bands (octaves); suitability of three different relevant image contrast metrics; experimental methodology for subjective tests; stimulus conditions. We finally present and discuss initial findings for all four measured sensitivities.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Triantaphillidou, J. Jarvis, G. Gupta, and H. Rana "Defining human contrast sensitivity and discrimination from complex imagery", Proc. SPIE 8901, Optics and Photonics for Counterterrorism, Crime Fighting and Defence IX; and Optical Materials and Biomaterials in Security and Defence Systems Technology X, 89010C (16 October 2013); https://doi.org/10.1117/12.2029194
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KEYWORDS
Visualization

Contrast sensitivity

Spatial frequencies

Data modeling

Signal detection

Image filtering

LCDs

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