Camera Image Quality Benchmarking contains the basic information and approaches for the use of subjectively correlated image quality metrics and outlines a framework for camera benchmarking. The authors show how to quantitatively compare image quality of cameras used for consumer photography. This book helps to fill a void in the literature by detailing the types of objective and subjective metrics that are fundamental to benchmarking still and video imaging devices. Specifically, the book provides an explanation of individual image quality attributes and how they manifest themselves to camera components and explores the key photographic still and video image quality metrics. The text also includes illustrative examples of benchmarking methods so that the practitioner can design a methodology appropriate to the photographic usage in consideration.
The authors outline the various techniques used to correlate the measurement results from the objective methods with subjective results. The text also contains a detailed description on how to set up an image quality characterization lab, with examples where the methodological benchmarking approach described has been implemented successfully. This vital resource:Explains in detail the entire process behind performing a complete characterization and benchmarking of cameras through image quality analysis Provides best practice measurement protocols and methodologies, so readers can develop and define their own camera benchmarking system to industry standards Includes many photographic images and diagrammatical illustrations to clearly convey image quality concepts Champions benchmarking approaches that value the importance of perceptually correlated image quality metrics
Written for image scientists, engineers, or managers involved in image quality and evaluating camera performance, Camera Image Quality Benchmarking combines knowledge from many different engineering fields, correlating objective (perception-independent) image quality with subjective (perception-dependent) image quality metrics.
In twenty-five pioneering and incisive essays, this unique digital field guide offers innovative new approaches to digital scholarship, the design of digital tools and objects, and the deployment of critically grounded technologies for analysis and discovery. Contributors cover a broad range of topics, including software development, hackathons, digitized objects, diversity in the tech sector, and distributed scientific collaborations. They discuss methodological considerations of social networks and data analysis, design projects that can translate STS concepts into durable scientific work, and much more.
Featuring a concise introduction by Janet Vertesi and David Ribes and accompanied by an interactive microsite, this book provides new perspectives on digital scholarship that will shape the agenda for tomorrow’s generation of STS researchers and practitioners.
Global warming skeptics often fall back on the argument that the scientific case for global warming is all model predictions, nothing but simulation; they warn us that we need to wait for real data, “sound science.” In A Vast Machine Paul Edwards has news for these skeptics: without models, there are no data. Today, no collection of signals or observations—even from satellites, which can “see” the whole planet with a single instrument—becomes global in time and space without passing through a series of data models. Everything we know about the world's climate we know through models. Edwards offers an engaging and innovative history of how scientists learned to understand the atmosphere—to measure it, trace its past, and model its future.
Representation in Scientific Practice, published by the MIT Press in 1990, helped coalesce a long-standing interest in scientific visualization among historians, philosophers, and sociologists of science and remains a touchstone for current investigations in science and technology studies. This volume revisits the topic, taking into account both the changing conceptual landscape of STS and the emergence of new imaging technologies in scientific practice. It offers cutting-edge research on a broad array of fields that study information as well as short reflections on the evolution of the field by leading scholars, including some of the contributors to the 1990 volume.
The essays consider the ways in which viewing experiences are crafted in the digital era; the embodied nature of work with digital technologies; the constitutive role of materials and technologies—from chalkboards to brain scans—in the production of new scientific knowledge; the metaphors and images mobilized by communities of practice; and the status and significance of scientific imagery in professional and popular culture.
Morana Alac, Michael Barany, Anne Beaulieu, Annamaria Carusi, Catelijne Coopmans, Lorraine Daston, Sarah de Rijcke, Joseph Dumit, Emma Frow, Yann Giraud, Aud Sissel Hoel, Martin Kemp, Bruno Latour, John Law, Michael Lynch, Donald MacKenzie, Cyrus Mody, Natasha Myers, Rachel Prentice, Arie Rip, Martin Ruivenkamp, Lucy Suchman, Janet Vertesi, Steve Woolgar