Addressing the many advances in imaging, computing, and communications technologies, this reference strikes just the right balance of coverage between core fundamental principles and the latest developments in this area. Its content was designed based on the idea that the reproducibility of published works on algorithms makes it easier for researchers to build on each other?s work, which often benefits the vitality of the technical community as a whole. For that reason, this book is as experimentally reproducible as possible.
Topics covered include:
Image denoising and deblurring
Different image restoration methods and recent advances such as nonlocality and sparsity
Blind restoration under space-varying blur
Super-resolution restoration
Learning-based methods
Multi-spectral and color image restoration
New possibilities using hybrid imaging systems
Many existing references are scattered throughout the literature, and there is a significant gap between the cutting edge in image restoration and what we can learn from standard image processing textbooks. To fill that need but avoid a rehash of the many fine existing books on this subject, this reference focuses on algorithms rather than theories or applications. Giving readers access to a large amount of downloadable source code, the book illustrates fundamental techniques, key ideas developed over the years, and the state of the art in image restoration. It is a valuable resource for readers at all levels of understanding.
