- Author:
- Aggelos K. Katsaggelos
The field of digital image restoration is concerned with the reconstruction or estimation of uncorrupted images from noisy, blurred ones. This blurring may be caused by optical distortions, object motion during imaging, or atmospheric turbulence. There are existing or potential applications of image restoration in many scientific and engineering fields, e.g. aerial imaging, remote sensing electron microscopy, and medical imaging. This book describes recent advances and provides a survey of the field. New research results are presented on the formulation of the restoration problem, the implementation of restoration algorithms using artificial neural networks, the derivation and application of nonstationary mathematical image models, the development of simultaneous image and blur parameter identification and restoration algorithms, and the development of algorithms for restoring scanned photographic images. Special attention is paid to issues of numerical instrumentation. A large number of illustrations demonstrate the performance of the restoration approaches.
Cited By
- Ivanov B, Milovanović G and Stanimirović P (2023). Accelerated Dai-Liao projection method for solving systems of monotone nonlinear equations with application to image deblurring, Journal of Global Optimization, 85:2, (377-420), Online publication date: 1-Feb-2023.
- Mao X, Liu Y, Liu F, Li Q, Shen W and Wang Y Intriguing findings of frequency selection for image deblurring Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence and Thirty-Fifth Conference on Innovative Applications of Artificial Intelligence and Thirteenth Symposium on Educational Advances in Artificial Intelligence, (1905-1913)
- Yao D, McLaughlin S and Altmann Y (2022). Fast Scalable Image Restoration Using Total Variation Priors and Expectation Propagation, IEEE Transactions on Image Processing, 31, (5762-5773), Online publication date: 1-Jan-2022.
- Chantas G, Nikolopoulos S and Kompatsiaris I (2020). Heavy-Tailed Self-Similarity Modeling for Single Image Super Resolution, IEEE Transactions on Image Processing, 30, (838-852), Online publication date: 1-Jan-2021.
- Scetbon M, Elad M and Milanfar P (2021). Deep K-SVD Denoising, IEEE Transactions on Image Processing, 30, (5944-5955), Online publication date: 1-Jan-2021.
- Hong Q, Li Y and Wang X (2019). Memristive continuous Hopfield neural network circuit for image restoration, Neural Computing and Applications, 32:12, (8175-8185), Online publication date: 1-Jun-2020.
- Joudar N and Ettaouil M (2019). Mathematical mixed-integer programming for solving a new optimization model of selective image restoration, Circuits, Systems, and Signal Processing, 38:5, (2072-2096), Online publication date: 1-May-2019.
- Bongini P, Del Chiaro R, Bagdanov A and Del Bimbo A GADA: Generative Adversarial Data Augmentation for Image Quality Assessment Image Analysis and Processing – ICIAP 2019, (214-224)
- Badoual A, Fageot J and Unser M (2018). Periodic Splines and Gaussian Processes for the Resolution of Linear Inverse Problems, IEEE Transactions on Signal Processing, 66:22, (6047-6061), Online publication date: 15-Nov-2018.
- Chen L, Zhou S and Zhang Z (2018). SVRG for a non-convex problem using graduated optimization algorithm, Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 34:1, (153-165), Online publication date: 1-Jan-2018.
- Skariah D and Arigovindan M (2017). Nested Conjugate Gradient Algorithm With Nested Preconditioning for Non-Linear Image Restoration, IEEE Transactions on Image Processing, 26:9, (4471-4482), Online publication date: 1-Sep-2017.
- Tagliasacchi M, Visentini-Scarzanella M, Dragotti P and Tubaro S (2016). Identification of Transform Coding Chains, IEEE Transactions on Image Processing, 25:3, (1109-1123), Online publication date: 1-Mar-2016.
- Xu Zhou , Mateos J, Fugen Zhou , Molina R and Katsaggelos A (2015). Variational Dirichlet Blur Kernel Estimation, IEEE Transactions on Image Processing, 24:12, (5127-5139), Online publication date: 1-Dec-2015.
- Saipullah K and Kim D (2012). A robust texture feature extraction using the localized angular phase, Multimedia Tools and Applications, 59:3, (717-747), Online publication date: 1-Aug-2012.
- Ramakrishnan N, Ertin E and Moses R (2010). Enhancement of coupled multichannel images using sparsity constraints, IEEE Transactions on Image Processing, 19:8, (2115-2126), Online publication date: 1-Aug-2010.
- Tzeng J, Liu C and Nguyen T (2010). Contourlet domain multiband deblurring based on color correlation for fluid lens cameras, IEEE Transactions on Image Processing, 19:10, (2659-2668), Online publication date: 1-Oct-2010.
- Zhu H, Liu M, Ji H and Li Y (2010). Combined invariants to blur and rotation using Zernike moment descriptors, Pattern Analysis & Applications, 13:3, (309-319), Online publication date: 1-Aug-2010.
- Belekos S, Galatsanos N and Katsaggelos A (2010). Maximum a posteriori video super-resolution using a new multichannel image prior, IEEE Transactions on Image Processing, 19:6, (1451-1464), Online publication date: 1-Jun-2010.
- Seghouane A (2009). Model selection criteria for image restoration, IEEE Transactions on Neural Networks, 20:8, (1357-1363), Online publication date: 1-Aug-2009.
- Tzeng J and Nguyen T (2009). Image enhancement for fluid lens camera based on color correlation, IEEE Transactions on Image Processing, 18:4, (729-739), Online publication date: 1-Apr-2009.
- Chen F and Ma J (2009). An empirical identification method of Gaussian blur parameter for image deblurring, IEEE Transactions on Signal Processing, 57:7, (2467-2478), Online publication date: 1-Jul-2009.
- Zheng H and Hellwich O Extended mumford-shah regularization in bayesian estimation for blind image deconvolution and segmentation Proceedings of the 11th international conference on Combinatorial Image Analysis, (144-158)
- Zheng H and Hellwich O Double regularized bayesian estimation for blur identification in video sequences Proceedings of the 7th Asian conference on Computer Vision - Volume Part II, (943-952)
- Zhou X, Zhou F and Bai X Parameter estimation for L
P regularized image deconvolution 2015 IEEE International Conference on Image Processing (ICIP), (4892-4896)
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