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.
© 2014 Optical Society of America
Original Manuscript: February 13, 2014
Revised Manuscript: April 8, 2014
Manuscript Accepted: April 9, 2014
Published: June 30, 2014
Richard G. Paxman, David A. Carrara, Paul D. Walker, and Nicolas Davidenko, "Silhouette estimation," J. Opt. Soc. Am. A 31, 1636-1644 (2014)