Intro; Preface; Contents; Part I Image Reconstruction from Incomplete Data; 1 Adaptive Regularization for Image Reconstruction from Subsampled Data; Introduction; Problem Settings and Notations; Adaptive Regularization Approach; ROF-Model and Surrogate Iteration; Hierarchical Spatially Adaptive Algorithm; Numerical Experiments; Reconstruction of Partial Fourier Data; Wavelet Inpainting; Qualitative Relation to Other Spatially Distributed Parameter Methods; Conclusion; References; 2 A Convergent Fixed-Point Proximity Algorithm Accelerated by FISTA for the 0 Sparse Recovery Problem

IntroductionMinimizers of the Proposed Model; Convergence Analysis of the Proposed Algorithms; Sparse Support Pursuit; Recovery on the Sparse Support; Numerical Experiments; Conclusion; References; 3 Sparse-Data Based 3D Surface Reconstructionfor Cartoon and Map; Introduction; Proposed Model; Augmented Lagrangian Method; Solving the Q-Subproblem (3.7); Solving the P-Subproblem (3.8); Solving the C-Subproblem (3.9); Solving the S-Subproblem (3.10); Solving the I-Subproblem (3.11); Solving the E-Subproblem (3.12); Numerical Results; Conclusion; References

Part II Image Enhancement, Restoration and Registration4 Variational Methods for Gamut Mappingin Cinema and Television; Introduction; Related Work; Gamut Reduction Algorithms (GRAs); Gamut Extension Algorithms (GEAs); Reproduction Intent and Evaluation; Subjective Evaluation; Objective Evaluation; Gamut Mapping in RGB Based on Perceptually-Based Color and Contrast Enhancement; GRA-RGB Zamir2014: Gamut Reduction Algorithm on RGB; GEA-RGB Zamir2014: Gamut Extension Algorithm on RGB; Gamut Extension in CIELAB Color Space; GEA-LAB1 Zamir2015: Gamut Extension Algorithm

GEA-LAB2 Zamir2017: Gamut Extension Algorithm Driven by Hue, Saturation and Chroma ConstraintsQualitative Experiments and Results; Methodology; Results; Temporal Consistency Test; Gamut Mapping Using Kernel Based Retinex (KBR) in HSV Color Space; GEA-KBR Zamir2016: Gamut Extension Algorithm; Results of GEA-KBR; Making the GEA-KBR Faster; GRA-KBR: Gamut Reduction Algorithm; Results of GRA-KBR; Conclusion and Future Work; References; 5 Functional Lifting for Variational Problems with Higher-Order Regularization; Introduction and Related Work; Contributions

Lifting for Absolute Laplacian RegularizationNotation and Mathematical Preliminaries; Approximate Relaxation of the Absolute Laplacian; Experimental Results; Non-convex Denoising with Second-Order Regularity; Image Registration Using the Absolute Laplacian; Translation-Only Synthetic Image; Real-World Image Registration; Conclusion and Outlook; References; 6 On the Convex Model of Speckle Reduction; Introduction; A Convex Model for Despeckling; Speckle Noise; Convex Variational Model for Despeckling; Numerical Scheme Using Bermudez-Moreno Algorithm; Generalized Form