This book’s treatment of image deblurring is unique in two ways: it includes algorithmic and implementation details; and by keeping the formulations in terms of matrices, vectors, and matrix computations, it makes the material accessible to a wide range of readers.
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Editorial Reviews
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'The book’s focus on imaging problems is very unique among the competing books on inverse and ill-posed problems. …It gives a nice introduction into the MATLAB world of images and deblurring problems.' Martin Hanke, Professor, Institut für Mathematik, Johannes-Gutenberg-Universität
Book Description
This book’s treatment of image deblurring is unique in two ways: it includes algorithmic and implementation details; and by keeping the formulations in terms of matrices, vectors, and matrix computations, it makes the material accessible to a wide range of readers.
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4.0 out of 5 stars
Excellent book on Deblurring images,
By PC (L.A., CA United States) - See all my reviews
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This review is from: Deblurring Images: Matrices, Spectra, and Filtering (Fundamentals of Algorithms 3) (Paperback)
I enjoy reading this book very much. From introductory material to algorithmic and implementation details, it is packed with interesting material.
I especially like the `Pointer' and `Very Important Point (VIP)' sections throughout the book. Many times, the VIP and Pointer sections help me focus on what was covered even though the material may be a bit unclear to me or I may have forgotten a piece of the mathematics. Another nice feature is that you don't need to have MATLAB Image Processing Toolbox (IPT) to implement the algorithm in the book, the authors provide a HNO MATLAB package to supplement the IPT functions. To understand the material, you should be comfortable with numerical analysis and linear algebra. A good grasp on Numerical Linear algebra at Demmel's or Trefethen's or Golub's book would not hurt. My minor complaint is the high price for such a small book. Highly recommended. A real gem!
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Inside This Book
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Key Phrases - Statistically Improbable Phrases (SIPs):
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structured matrix computations, reflexive boundary conditions, image deblurring problems, inverted noise, blurring matrix, blurring model, deblurring images, smoothing norms, regularization error, perturbation error, regularized solution, filter factors, regularization parameter, residual norm, generalized cross validation, structured matrices, naïve solution, spectral filtering, zero boundary conditions, singular vectors New!
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Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
structured matrix computations, reflexive boundary conditions, image deblurring problems, inverted noise, blurring matrix, blurring model, deblurring images, smoothing norms, regularization error, perturbation error, regularized solution, filter factors, regularization parameter, residual norm, generalized cross validation, structured matrices, naïve solution, spectral filtering, zero boundary conditions, singular vectors New!
Books on Related Topics | Concordance | Text Stats Browse Sample Pages:
Front Cover | Table of Contents | First Pages | Index | Back Cover | Surprise Me!
Citations (learn more)
This book cites 6
books:
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- Computational Frameworks for the Fast Fourier Transform (Frontiers in Applied Mathematics) by Charles Van Loan in Back Matter (1), and Back Matter (2)
- Fundamentals of Digital Image Processing by Anil K. Jain in Back Matter (1), and Back Matter (2)
- Imaging Through Turbulence (Laser & Optical Science & Technology) by Michael C. Roggemann in Back Matter
- Matrix Computations (Johns Hopkins Studies in Mathematical Sciences)(3rd Edition) by Gene H. Golub in Back Matter
- Matrix Algorithms by G. W. Stewart in Back Matter
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