Split Bregman iteration algorithm for total bounded variation regularization based image deblurring
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Publication:994320
DOI10.1016/j.jmaa.2010.07.013zbMath1202.94062OpenAlexW2051974992MaRDI QIDQ994320
Publication date: 17 September 2010
Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmaa.2010.07.013
Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
Related Items (13)
Total bounded variation-based Poissonian images recovery by split Bregman iteration ⋮ Split Bregman iteration algorithm for image deblurring using fourth-order total bounded variation regularization model ⋮ Multi and hyperspectral image unmixing with spatial coherence by extended blind end-member and abundance extraction ⋮ Fixed-Point-like method for a new Total variation-based image restoration model ⋮ A PDE approach to image restoration problem with observation on a meager domain ⋮ A new nonlocal total variation regularization algorithm for image denoising ⋮ Runge-Kutta type total variation regularization for nonlinear inverse problems ⋮ Efficient algorithms for hybrid regularizers based image denoising and deblurring ⋮ An efficient variational method for image restoration ⋮ An augmented Lagrangian algorithm for total bounded variation regularization based image deblurring ⋮ An efficient algorithm for adaptive total variation based image decomposition and restoration ⋮ CT image reconstruction algorithms based on the Hanke Raus parameter choice rule ⋮ Non-local total bounded variation scheme for multiple-coil magnetic resonance image restoration
Uses Software
Cites Work
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