The Weight of Images explores the ways in which media images can train their viewers’ bodies. Proposing a shift away from an understanding of spectatorship as being constituted by acts of the mind, this book favours a theorization of relations between bodies and images as visceral, affective engagements that shape our body image - with close attention to one particularly charged bodily characteristic in contemporary western culture: fat. The first mapping of the ways in which fat, gendered bodies are represented across a variety of media forms and genres, from reality television to Hollywood movies, from TV sitcoms to documentaries, from print magazine and news media to online pornography, The Weight of Images contends that media images of fat bodies are never only about fat; rather, they are about our relation to corporeal vulnerability overall. A ground-breaking volume, engaging with a rich variety of media and cultural texts, whilst examining the possibilities of critical auto-ethnography to unravel how body images take shape affectively between bodies and images, this book will appeal to scholars and students of sociology, media, cultural and gender studies, with interests in embodiment and affect.

Presents a review of image denoising algorithms with practical MATLAB implementation guidance Digital Image Denoising in MATLAB provides a comprehensive treatment of digital image denoising, containing a variety of techniques with applications in high-quality photo enhancement as well as multi-dimensional signal processing problems such as array signal processing, radar signal estimation and detection, and more. Offering systematic guidance on image denoising in theories and in practice through MATLAB, this hands-on guide includes practical examples, chapter summaries, analytical and programming problems, computer simulations, and source codes for all algorithms discussed in the book. The book explains denoising algorithms including linear and nonlinear filtering, Wiener filtering, spatially adaptive and multi-channel processing, transform and wavelet domains processing, singular value decomposition, and various low variance optimization and low rank processing techniques. Throughout the text, the authors address the theory, analysis, and implementation of the denoising algorithms to help readers solve their image processing problems and develop their own solutions. Explains how the quality of an image can be quantified in MATLAB Discusses what constitutes a “naturally looking” image in subjective and analytical terms Presents denoising techniques for a wide range of digital image processing applications Describes the use of denoising as a pre-processing tool for various signal processing applications or big data analysis Requires only a fundamental knowledge of digital signal processing Includes access to a companion website with source codes, exercises, and additional resources Digital Image Denoising in MATLAB is an excellent textbook for undergraduate courses in digital image processing, recognition, and statistical signal processing, and a highly useful reference for researchers and engineers working with digital images, digital video, and other applications requiring denoising techniques.

What do they all mean – the lascivious ape, autophagic dragons, pot-bellied heads, harp-playing asses, arse-kissing priests and somersaulting jongleurs to be found protruding from the edges of medieval buildings and in the margins of illuminated manuscripts? Michael Camille explores that riotous realm of marginal art, so often explained away as mere decoration or zany doodles, where resistance to social constraints flourished. Medieval image-makers focused attention on the underside of society, the excluded and the ejected. Peasants, servants, prostitutes and beggars all found their place, along with knights and clerics, engaged in impudent antics in the margins of prayer-books or, as gargoyles, on the outsides of churches. Camille brings us to an understanding of how marginality functioned in medieval culture and shows us just how scandalous, subversive, and amazing the art of the time could be.

Consistently rated as the best overall introduction to computer-based image processing, The Image Processing Handbook covers two-dimensional (2D) and three-dimensional (3D) imaging techniques, image printing and storage methods, image processing algorithms, image and feature measurement, quantitative image measurement analysis, and more. Incorporating image processing and analysis examples at all scales, from nano- to astro-, this Seventh Edition: Features a greater range of computationally intensive algorithms than previous versions Provides better organization, more quantitative results, and new material on recent developments Includes completely rewritten chapters on 3D imaging and a thoroughly revamped chapter on statistical analysis Contains more than 1700 references to theory, methods, and applications in a wide variety of disciplines Presents 500+ entirely new figures and images, with more than two-thirds appearing in color The Image Processing Handbook, Seventh Edition delivers an accessible and up-to-date treatment of image processing, offering broad coverage and comparison of algorithms, approaches, and outcomes.

Examines the imperial mythology that was reflected by Roman art and architecture during the rule of Augustus Caesar