title: Silhouette estimation.
abstract: 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.
authors.forename: Richard G
authors.initials: RG
authors.lastname: Paxman
authors.forename: David A
authors.initials: DA
authors.lastname: Carrara
authors.forename: Paul D
authors.initials: PD
authors.lastname: Walker
authors.forename: Nicolas
authors.initials: N
authors.lastname: Davidenko
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001699:Biometry / Q000379:methods*; D005145:Face / Q000033:anatomy & histology*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*