This book represents a sample of recent contributions of researchers all around the world in the field of image restoration. The book consists of 15 chapters organized in three main sections (Theory, Applications, Interdisciplinarity). Topics cover some different aspects of the theory of image restoration, but this book is also an occasion to highlight some new topics of research related to the emergence of some original imaging devices. From this arise some real challenging problems related to image reconstruction/restoration that open the way to some new fundamental scientific questions closely related with the world we interact with.

One of the most intriguing questions in image processing is the problem of recovering the desired or perfect image from a degraded version. In many instances one has the feeling that the degradations in the image are such that relevant information is close to being recognizable, if only the image could be sharpened just a little. This monograph discusses the two essential steps by which this can be achieved, namely the topics of image identification and restoration. More specifically the goal of image identifi cation is to estimate the properties of the imperfect imaging system (blur) from the observed degraded image, together with some (statistical) char acteristics of the noise and the original (uncorrupted) image. On the basis of these properties the image restoration process computes an estimate of the original image. Although there are many textbooks addressing the image identification and restoration problem in a general image processing setting, there are hardly any texts which give an indepth treatment of the state-of-the-art in this field. This monograph discusses iterative procedures for identifying and restoring images which have been degraded by a linear spatially invari ant blur and additive white observation noise. As opposed to non-iterative methods, iterative schemes are able to solve the image restoration problem when formulated as a constrained and spatially variant optimization prob In this way restoration results can be obtained which outperform the lem. results of conventional restoration filters.

Recent research results are presented regarding the formulation of the restoration problem as a convex programming problem, the implementation of restoration algorithms using artificial neural networks, the derivation of non-stationary image models and their application to image estimation and restoration, the development of algorithms for the simultaneous image and blur parameter identification and restoration, and the development of algorithms for restoring scanned photographic images.

Image Restoration: Fundamentals and Advances responds to the need to update most existing references on the subject, many of which were published decades ago. Providing a broad overview of image restoration, this book explores breakthroughs in related algorithm development and their role in supporting real-world applications associated with various scientific and engineering fields. These include astronomical imaging, photo editing, and medical imaging, to name just a few. The book examines how such advances can also lead to novel insights into the fundamental properties of image sources. 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.

This book shows there is a profound connection between information and entropy. Without this connection, information would be more difficult to apply to science. This book covers the connection and the application to modern optics and radar imaging. It shows that there exists a profound relationship between Einstein’s relativity theory and Schröinger’s quantum mechanics, by means of the uncertainty principle. In due of the uncertainty relation, this book shows that every bit of information takes time and energy to transfer, to create and to observe. The new edition contains 3 new chapters on radar imaging with optics, science in the myth of information, and time and the enigma of space.

Digital Image Enhancement, Restoration and Compression focuses on human vision-based imaging application development. Examples include making poor images look better, the development of advanced compression algorithms, special effects imaging for motion pictures and the restoration of satellite images distorted by atmospheric disturbance. This book presents a unique engineering approach to the practice of digital imaging, which starts by presenting a global model to help gain an understanding of the overall process, followed by a breakdown and explanation of each individual topic. Topics are presented as they become necessary for understanding the practical imaging model under study, which provides the reader with the motivation to learn about and use the tools and methods being explored. The book includes chapters on imaging systems and software, the human visual system, image transforms, image filtering, image enhancement, image restoration, and image compression. Numerous examples, including over 700 color images, are used to illustrate the concepts discussed. Readers can explore their own application development with any programming language, including C/C++, MATLAB®, Python and R, and software is provided for both the Windows/C/C++ and MATLAB environments. The book can be used by the academic community in teaching and research, with over 1,000 PowerPoint slides and a complete solutions manual to the over 230 included problems. It can also be used for self-study by those involved with application development, whether they are engineers, scientists or artists. The new edition has been extensively updated and includes numerous problems and programming exercises that will help the reader and student develop their skills.

This book provides an in-depth treatment of the three important topics related to image and video databases: restoration, watermarking and retrieval. It is the result of the participation of the Delft University of Technology in the European Union ACTS program, a pre-competitive R&D program on Advanced Communications Technologies and Services (1994-1998). In particular the book has benefited from participation in the AURORA and SMASH projects respectively automated film and video restoration and storage for multimedia systems (watermarking & retrieval).

It is essential that differently oriented specialists and students involved in image processing have a firm grasp of the necessary concepts and principles. A single-source reference that can provide this foundation, as well as a thorough explanation of the techniques involved, particularly those found in medical image processing, would be an