title: A wavelet-laplace variational technique for image deconvolution and inpainting.
abstract: We construct a new variational method for blind deconvolution of images and inpainting, motivated by recent PDE-based techniques involving the Ginzburg-Landau functional, but using more localized wavelet-based methods. We present results for both binary and grayscale images. Comparable speeds are achieved with better sharpness of edges in the reconstruction.
authors.affiliation: Department of Mathematics, University of California, Los Angeles, CA 90095, USA. juliadob@math.ucla.edu
authors.forename: Julia A
authors.initials: JA
authors.lastname: Dobrosotskaya
authors.forename: Andrea L
authors.initials: AL
authors.lastname: Bertozzi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003196:Computer Graphics; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010151:Paintings; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted