A Wavelet-Laplace Variational Technique for Image Deconvolution and Inpainting

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 ac...

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Bibliographic Details
Published in:IEEE transactions on image processing 2008-05, Vol.17 (5), p.657-663
Main Authors: Dobrosotskaya, J.A., Bertozzi, A.L.
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Artificial Intelligence
Barcode
binary image
Blinds
Computer Graphics
Construction
Deconvolution
Detection, estimation, filtering, equalization, prediction
Discrete wavelet transforms
Exact sciences and technology
Image analysis
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Image processing
Information, signal and communications theory
inpainting
Miscellaneous
Pattern Recognition, Automated - methods
Reconstruction
Reproducibility of Results
Sensitivity and Specificity
Sharpness
Signal analysis
Signal and communications theory
Signal processing
Signal Processing, Computer-Assisted
Signal, noise
Telecommunications and information theory
Variational methods
Wavelet analysis
Wavelet coefficients
wavelet diffusion
Wavelet domain
Wavelet packets
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Description
Summary: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.
ISSN:1057-7149
1941-0042
DOI:10.1109/TIP.2008.919367