7 March 2018 Towards a surround-aware numerical observer
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Abstract
Motivated by the fact that the visibility of an object is affected by its surrounding brightness, we design a surround-aware anthropomorphic numerical observer and conduct experiments to validate it. We derive the observer based on Barten’s formula that predicts the visibility of a sinusoidal pattern in a large uniformly lit surround field. The following are the key steps as well as assumptions in observer derivation. We deduce the effect of a ring-shaped surround from the predicted visibility thresholds for two large surrounds with different eccentricities from the target. Moreover, we theorize that the visibility of a small round object (akin to a micro-calcification in a breast radiograph) is the same as a single cycle of a sinusoid. Assuming independent detection of sinusoid cycles, we calculate the visibility threshold for a single cycle target from that of a multicycle sinusoidal pattern, which is predicted by Barten’s formula. The validation experiments are set up to isolate the effects of surround luminance, its eccentricity from the target, and its size. Our experimental results indicate that a surround considerably different from the target in luminance hinders target’s visibility. Moreover, we observer that the surround size and its proximity to the target tend to increase its impact. These observations are predicted by the proposed numerical observer. We also note that a dark surround seems to adversely affect the visibility of a bright target considerably more than a bright surround affects the visibility of a dark target. This asymmetry, however, cannot be predicted by the proposed observer.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ali R. N. Avanaki, Ali R. N. Avanaki, Kathryn S. Espig, Kathryn S. Espig, Albert Xthona, Albert Xthona, Tom R. L. Kimpe, Tom R. L. Kimpe, } "Towards a surround-aware numerical observer", Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 105770R (7 March 2018); doi: 10.1117/12.2294570; https://doi.org/10.1117/12.2294570
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