Covering ideas and methods while concentrating on fundamentals, this book includes wave motion; digital imaging; digital filtering; visualization aspects of the seismic reflection method; sampling theory; the frequency spectrum; synthetic seismograms; wavelet processing; deconvolution; seismic attributes; phase rotation; and seismic attenuation.

Blind image deconvolution is constantly receiving increasing attention from the academic as well the industrial world due to both its theoretical and practical implications. The field of blind image deconvolution has several applications in different areas such as image restoration, microscopy, medical imaging, biological imaging, remote sensing, astronomy, nondestructive testing, geophysical prospecting, and many others. Blind Image Deconvolution: Theory and Applications surveys the current state of research and practice as presented by the most recognized experts in the field, thus filling a gap in the available literature on blind image deconvolution. Explore the gamut of blind image deconvolution approaches and algorithms that currently exist and follow the current research trends into the future. This comprehensive treatise discusses Bayesian techniques, single- and multi-channel methods, adaptive and multi-frame techniques, and a host of applications to multimedia processing, astronomy, remote sensing imagery, and medical and biological imaging at the whole-body, small-part, and cellular levels. Everything you need to step into this dynamic field is at your fingertips in this unique, self-contained masterwork. For image enhancement and restoration without a priori information, turn to Blind Image Deconvolution: Theory and Applications for the knowledge and techniques you need to tackle real-world problems.

This book discusses the use of digital image processing technologies in a wide range of industries. Using machine learning approaches, readers will get an understanding of the many technologies and tactics utilized in the digital image processing and the management of large amounts of data. Students and scholars in topics including engineering, agricultural, and medical image processing would find this book useful in further developing their expertise in these areas. This work is aimed at students with some background in mathematics or computer science, and it uses examples written in the programming language Matlab to introduce and clarify some of the fundamental ideas behind contemporary pattern recognition and image processing techniques. The focus is on application rather than theory, and the book provides a context for understanding the ideas through a sequence of carefully selected examples, activities, and computer experiments that rely on real-world applications in the fields of science, healthcare, and engineering. This book covers important topic like Understanding an image, Resolution and quantization, Bit-plane splicing, Pixels, Image restoration, Blind deconvolution, Shape iv transformation and homogeneous coordinates, Morphological processing, Dilation, erosion and structuring elements within Matlab, The hit-or-miss transformation, Image segmentation and many more.

In recent years, Moore's law has fostered the steady growth of the field of digital image processing, though the computational complexity remains a problem for most of the digital image processing applications. In parallel, the research domain of optical image processing has matured, potentially bypassing the problems digital approaches were suffering and bringing new applications. The advancement of technology calls for applications and knowledge at the intersection of both areas but there is a clear knowledge gap between the digital signal processing and the optical processing communities. This book covers the fundamental basis of the optical and image processing techniques by integrating contributions from both optical and digital research communities to solve current application bottlenecks, and give rise to new applications and solutions. Besides focusing on joint research, it also aims at disseminating the knowledge existing in both domains. Applications covered include image restoration, medical imaging, surveillance, holography, etc... "a very good book that deserves to be on the bookshelf of a serious student or scientist working in these areas." Source: Optics and Photonics News

Fully updated, the second edition of this book covers the widespread advances in digital imaging technology, techniques, and devices. It discusses the increased power, storage capacity, and use of digital cameras, laptop computers, tablets, and cell phones in forensic science. It addresses methods for presenting evidence in a courtroom, including under Frye and Daubert rules. It also explains concepts with minimal jargon, making it accessible to a wide range of photography, criminal justice, forensic, and legal professionals.

Describes the deblurring algorithms and techniques collectively known as spectral filtering methods, in which the singular value decomposition, or a similar decomposition with spectral properties, is used to introduce the necessary regularization or filtering in the reconstructed image. The concise MATLAB® implementations described in the book provide a template of techniques that can be used to restore blurred images from many applications.