Image Problems

This deft and lively study by Robert DeCaroli explores the questions of how and why the earliest verifiable images of the historical Buddha were created. In so doing, DeCaroli steps away from old questions of where and when to present the history of Buddhism�s relationship with figural art as an ongoing set of negotiations within the Buddhist community and in society at large. By comparing innovations in Brahmanical, Jain, and royal artistic practice, DeCaroli examines why no image of the Buddha was made until approximately five hundred years after his death and what changed in the centuries surrounding the start of the Common Era to suddenly make those images desirable and acceptable. The textual and archaeological sources reveal that figural likenesses held special importance in South Asia and were seen as having a significant amount of agency and power. Anxiety over image use extended well beyond the Buddhists, helping to explain why images of Vedic gods, Jain teachers, and political elites also are absent from the material record of the centuries BCE. DeCaroli shows how the emergence of powerful dynasties and rulers, who benefited from novel modes of visual authority, was at the root of the changes in attitude toward figural images. However, as DeCaroli demonstrates, a strain of unease with figural art persisted, even after a tradition of images of the Buddha had become established.

Many people occasionally suffer from a negative body self-image but, for an increasing number of people, this can turn into a more serious preoccupation. One per cent of the population will develop Body Dysmorphic Disorder (BDD), a condition characterised by severe preoccupation with a perceived physical defect. Body image problems can cause significant distress and can lead to further problems such as anxiety, eating disorders and social phobia. It has long been recognised that negative body image problems are a factor in the onset and maintenance of many eating disorders. However, they can be successfully treated with cognitive behavioral therapy (CBT). Praise for Overcoming Obsessive Compulsive Disorder and the Overcoming series: '[Overcoming Obsessive Compulsive Disorder] is an affordable and highly recommended read.' The Psychologist 'The best consumer-friendly CBT-based books...All are very thorough.' Observer

This book contains the proceedings of the Special Session, Interaction of Inverse Problems and Image Analysis, held at the January 2001 meeting of the AMS in New Orleans, LA. The common thread among inverse problems, signal analysis, and image analysis is a canonical problem: recovering an object (function, signal, picture) from partial or indirect information about the object. Both inverse problems and imaging science have emerged in recent years as interdisciplinary research fields with profound applications in many areas of science, engineering, technology, and medicine. Research in inverse problems and image processing shows rich interaction with several areas of mathematics and strong links to signal processing, variational problems, applied harmonic analysis, and computational mathematics. This volume contains carefully referred and edited original research papers and high-level survey papers that provide overview and perspective on the interaction of inverse problems, image analysis, and medical imaging. The book is suitable for graduate students and researchers interested in signal and image processing and medical imaging.

Partial differential equations and variational methods were introduced into image processing about 15 years ago, and intensive research has been carried out since then. The main goal of this work is to present the variety of image analysis applications and the precise mathematics involved. It is intended for two audiences. The first is the mathematical community, to show the contribution of mathematics to this domain and to highlight some unresolved theoretical questions. The second is the computer vision community, to present a clear, self-contained, and global overview of the mathematics involved in image processing problems. The book is divided into five main parts. Chapter 1 is a detailed overview. Chapter 2 describes and illustrates most of the mathematical notions found throughout the work. Chapters 3 and 4 examine how PDEs and variational methods can be successfully applied in image restoration and segmentation processes. Chapter 5, which is more applied, describes some challenging computer vision problems, such as sequence analysis or classification. This book will be useful to researchers and graduate students in mathematics and computer vision.

This book contains eleven original and survey scientific research articles arose from presentations given by invited speakers at International Workshop on Image Processing and Inverse Problems, held in Beijing Computational Science Research Center, Beijing, China, April 21–24, 2018. The book was dedicated to Professor Raymond Chan on the occasion of his 60th birthday. The contents of the book cover topics including image reconstruction, image segmentation, image registration, inverse problems and so on. Deep learning, PDE, statistical theory based research methods and techniques were discussed. The state-of-the-art developments on mathematical analysis, advanced modeling, efficient algorithm and applications were presented. The collected papers in this book also give new research trends in deep learning and optimization for imaging science. It should be a good reference for researchers working on related problems, as well as for researchers working on computer vision and visualization, inverse problems, image processing and medical imaging.

The next generation of engineering and computing systems will be both complex and distributed in functionality due to a variety of information sources needed for their operation. Successful development and deployment of these systems critically depends on the mechanisms for acquisition, coordination, communication and integration of information from various components. This collection of papers addresses various aspects in the area of signal and image integration with a specific emphasis on parallel and distributed solutions. A wide spectrum of issues including image and signal processing, parallel architectures/algorithms, sensor integration/fusion, and neural networks/fuzzy systems, are addressed in various papers.

In the past few decades, imaging hardware has improved tremendously in terms of resolution, making widespread usage of images in many diverse applications on Earth and planetary missions. However, practical issues associated with image acquisition are still affecting image quality. Some of these issues such as blurring, measurement noise, mosaicing artifacts, low spatial or spectral resolution, etc. can seriously affect the accuracy of the aforementioned applications. This book intends to provide the reader with a glimpse of the latest developments and recent advances in image restoration, which includes image super-resolution, image fusion to enhance spatial, spectral resolution, and temporal resolutions, and the generation of synthetic images using deep learning techniques. Some practical applications are also included.

The focus of this book is on "ill-posed inverse problems". These problems cannot be solved only on the basis of observed data. The building of solutions involves the recognition of other pieces of a priori information. These solutions are then specific to the pieces of information taken into account. Clarifying and taking these pieces of information into account is necessary for grasping the domain of validity and the field of application for the solutions built. For too long, the interest in these problems has remained very limited in the signal-image community. However, the community has since recognized that these matters are more interesting and they have become the subject of much greater enthusiasm. From the application field’s point of view, a significant part of the book is devoted to conventional subjects in the field of inversion: biological and medical imaging, astronomy, non-destructive evaluation, processing of video sequences, target tracking, sensor networks and digital communications. The variety of chapters is also clear, when we examine the acquisition modalities at stake: conventional modalities, such as tomography and NMR, visible or infrared optical imaging, or more recent modalities such as atomic force imaging and polarized light imaging.