Explicit Algorithms for a New Time Dependent Model Based on Level Set Motion for Nonlinear Deblurring and Noise Removal

By Antonio Marquina, Stanley J. Osher. SIAM Journal on Scientific Computing, 2000

330 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Geophysics, Mathematical Physics

View Paper: https://www.semanticscholar.org/paper/3bb8919f2da1e0cd1c1f598058a7262cb3890c82

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Citations in the corpus

Recent Developments in Total Variation Image Restoration (2004, methodology): “Explicit schemes suggested in [20] for solving the above equation improve the CFL to ∆t ≤ c∆x(2) which is independent of |∇u|.”
Edge and line oriented contour detection: State of the art (2011, background): “Other extensions concern vector-valued images [45,46], images defined on graphs [46], deblurring application [47,48], and decomposition of an image into three components (filtered image, texture, and noise) [37].”
An Efficient Primal-Dual Hybrid Gradient Algorithm For Total Variation Image Restoration (2008, methodology): “The method is very slow due to the CFL stability constraints (see [16]).”
Image restoration: Total variation, wavelet frames, and beyond (2012, methodology): “To avoid this, [1, 10, 11] used a regularized parabolic term for (2.”
Image up-sampling using total-variation regularization with a new observation model (2005, methodology): “In that sense, an LSM for image deblurring and noise removal is given in [40].”
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction (2008, background): “presented in [9, 3, 8, 30], but expect their performance to be similar to SOCP because they also require solving large systems of linear equations at each iteration.”
Image Super-Resolution by TV-Regularization and Bregman Iteration (2008, background): “The main advantage of this model is that it recovers edges well and removes noise avoiding the ringing effect [12, 14, 15, 19].”
Image inpainting (2000, background): “Finally, let us note that the choice of a non-normaliz ed field !N instead of a normalized version of it allows for a simpler and more stable numerical scheme; see [17, 18].”