Silhouette estimation
Copyright policy )Silhouette estimation
Silhouettes arise in a variety of imaging scenarios. Pristine silhouettes are often degraded via blurring, detector sampling, and detector noise. We present a maximum a posteriori estimator for the restoration of parameterized facial silhouettes. Extreme dealiasing and dramatic superresolution, well beyond the diffraction limit, are demonstrated through the use of strong prior knowledge.
- University of California, San Francisco United States
Automated, Biometry, Optics, Optical Physics, Pattern Recognition, Image Enhancement, Pattern Recognition, Automated, Computer-Assisted, Opthalmology and Optometry, Face, Image Interpretation, Computer-Assisted, Photography, Humans, Electrical and Electronic Engineering, Artifacts, Image Interpretation, Algorithms
Automated, Biometry, Optics, Optical Physics, Pattern Recognition, Image Enhancement, Pattern Recognition, Automated, Computer-Assisted, Opthalmology and Optometry, Face, Image Interpretation, Computer-Assisted, Photography, Humans, Electrical and Electronic Engineering, Artifacts, Image Interpretation, Algorithms
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!