Basic principles of image processing and programming explained without college-level mathematics. This book explores image processing from several perspectives: the creative, the theoretical (mainly mathematical), and the programmatical. It explains the basic principles of image processing, drawing on key concepts and techniques from mathematics, psychology of perception, computer science, and art, and introduces computer programming as a way to get more control over image processing operations. It does so without requiring college-level mathematics or prior programming experience. The content is supported by PixelMath, a freely available software program that helps the reader understand images as both visual and mathematical objects. The first part of the book covers such topics as digital image representation, sampling, brightness and contrast, color models, geometric transformations, synthesizing images, stereograms, photomosaics, and fractals. The second part of the book introduces computer programming using an open-source version of the easy-to-learn Python language. It covers the basics of image analysis and pattern recognition, including edge detection, convolution, thresholding, contour representation, and K-nearest-neighbor classification. A chapter on computational photography explores such subjects as high-dynamic-range imaging, autofocusing, and methods for automatically inpainting to fill gaps or remove unwanted objects in a scene. Applications described include the design and implementation of an image-based game. The PixelMath software provides a “transparent” view of digital images by allowing the user to view the RGB values of pixels by zooming in on an image. PixelMath provides three interfaces: the pixel calculator; the formula page, an advanced extension of the calculator; and the Python window.

This book explores image processing from several perspectives: the creative, the theoretical (mainly mathematical), and the programmatical. It explains the basic principles of image processing, drawing on key concepts and techniques from mathematics, psychology of perception, computer science, and art, and introduces computer programming as a way to get more control over image processing operations. It does so without requiring college-level mathematics or prior programming experience. The content is supported by PixelMath, a freely available software program that helps the reader understand images as both visual and mathematical objects. The first part of the book covers such topics as digital image representation, sampling, brightness and contrast, color models, geometric transformations, synthesizing images, stereograms, photomosaics, and fractals. The second part of the book introduces computer programming using an open-source version of the easy-to-learn Python language. It covers the basics of image analysis and pattern recognition, including edge detection, convolution, thresholding, contour representation, and K-nearest-neighbor classification. A chapter on computational photography explores such subjects as high-dynamic-range imaging, autofocusing, and methods for automatically inpainting to fill gaps or remove unwanted objects in a scene. Applications described include the design and implementation of an image-based game. The PixelMath software provides a "transparent" view of digital images by allowing the user to view the RGB values of pixels by zooming in on an image. PixelMath provides three interfaces: the pixel calculator; the formula page, an advanced extension of the calculator; and the Python window.

Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something—an artery, a road, a DNA marker, an oil spill—from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over a two or higher dimensional space, and to which standard image-processing algorithms may not apply. There are many important data analysis methods developed in this text for such statistical image problems. Examples abound throughout remote sensing (satellite data mapping, data assimilation, climate-change studies, land use), medical imaging (organ segmentation, anomaly detection), computer vision (image classification, segmentation), and other 2D/3D problems (biological imaging, porous media). The goal, then, of this text is to address methods for solving multidimensional statistical problems. The text strikes a balance between mathematics and theory on the one hand, versus applications and algorithms on the other, by deliberately developing the basic theory (Part I), the mathematical modeling (Part II), and the algorithmic and numerical methods (Part III) of solving a given problem. The particular emphases of the book include inverse problems, multidimensional modeling, random fields, and hierarchical methods.

This book provides a comprehensive introduction to quantum image processing, which focuses on extending conventional image processing tasks to the quantum computing frameworks. It summarizes the available quantum image representations and their operations, reviews the possible quantum image applications and their implementation, and discusses the open questions and future development trends. It offers a valuable reference resource for graduate students and researchers interested in this emerging interdisciplinary field.

This book presents the user-facing aspects of digital media, from the web and computer games, to mobile technologies and social media, and demonstrates how these are continuously growing and developing. The convergence of IT, telecommunications, and media is bringing about a revolution in the way information is collected, stored, accessed and distributed. Rae Earnshaw's book explores the principal factors driving this and the ways in which social and cultural contexts are affected by media content. This is Professor Earnshaw's fourth book in a series that focuses on digital media and creativity, and through the use of Case Studies; the theoretical, practical and technical aspects of digital media are examined. Readers are informed about how the user as content creator, publisher and broadcaster is changing the traditional roles of news media, publishers and entertainment corporations. Topics such as the evolution of digital imaging and the phenomenon of social media are discussed in relation to this. Professor Earnshaw also demonstrates how changes in technology produce shifts in the ways that consumers utilize it, in an increasing variety of application domains such as e-books, digital cameras, Facebook and Twitter. State of the Art in Digital Media and Applications will be invaluable for readers that want a comprehensive look at how emerging digital media technologies are being used, and how they are transforming how we create, consume, exchange and manipulate media content.

This book is a comprehensive introduction to the rapidly developing field of modeling and characterization of PEM fuel cells. It focuses on i) fuel cell performance modeling and performance characterization applicable from single cells to stacks, ii) fundamental and advanced techniques for structural and compositional characterization of fuel cell components and iii) electrocatalyst design. Written by experts in this field, this book is an invaluable tool for graduate students and professionals.

Design Strategies for Reimagining the City is situated between projective geometry, optical science and architectural design. It draws together seemingly unrelated fields in a series of new digital design tools and techniques underpinned by tested prototypes. The book reveals how the relationship between architectural design and the ubiquitous urban camera can be used to question established structures of control and ownership inherent within the visual model of the Western canon. Using key moments from the broad trajectory of historical and contemporary representational mechanisms and techniques, it describes the image’s impact on city form from the inception of linear perspective geometry to the digital turn. The discussion draws upon combined fields of digital geometry, the pictorial adaptation of human optical cues of colour brightness and shape, and modern image-capture technology (webcams, mobile phones and UAVs) to demonstrate how the permeation of contemporary urban space by digital networks calls for new architectural design tools and techniques. A series of speculative drawings and architectural interventions that apply the new design tools and techniques complete the book. Aimed at researchers, academics and upper-level students in digital design and theory, it makes a timely contribution to the ongoing and broadly debated relationship between representation and architecture.