Publications by authors named "Stavri G Nikolov"
Selection of image fusion quality measures: objective, subjective, and metric assessment.
J Opt Soc Am A Opt Image Sci Vis
December 2007
Accurate quality assessment of fused images, such as combined visible and infrared radiation images, has become increasingly important with the rise in the use of image fusion systems. We bring together three approaches, applying two objective tasks (local target analysis and global target location) to two scenarios, together with subjective quality ratings and three computational metrics. Contrast pyramid, shift-invariant discrete wavelet transform, and dual-tree complex wavelet transform fusion are applied, as well as levels of JPEG2000 compression.
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- The interest in image fusion, which combines images from different sources like infrared and visible light, has spurred the development of better assessment methods for these fused images.
- Previous research using subjective ratings and computational metrics often did not align with actual human performance in tasks utilizing these fused images.
- The current study introduced eye-tracking to measure how well participants could follow a camouflaged person in various fused video formats, revealing that fused displays generally improved tracking accuracy compared to raw inputs, highlighting the potential for these new assessment methods.
How do we visually encode facial expressions? Is this done by viewpoint-dependent mechanisms representing facial expressions as two-dimensional templates or do we build more complex viewpoint independent three-dimensional representations? Recent facial adaptation techniques offer a powerful way to address these questions. Prolonged viewing of a stimulus (adaptation) changes the perception of subsequently viewed stimuli (an after-effect). Adaptation to a particular attribute is believed to target those neural mechanisms encoding that attribute.
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