This book constitutes the refereed proceedings of the Third Computational Color Imaging Workshop, CCIW 2010, held in Milan, Italy, in April 2010. The 16 revised full papers, presented together with three invited papers, were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on computational photography, color and perception, color imaging, and computational imaging.
We would like to welcome you to the proceedings of CCIW 2009, the Computational Color Imaging Workshop, held in Saint-Etienne, France, March 26–27, 2009. This, the second CCIW, was organized by the University Jean Monnet and the - boratoire Hubert Curien UMR 5516 (Saint-Etienne, France) with the endorsement of the International Association for Pattern Recognition (IAPR), the French Association for Pattern Recognition and Interpretation (AFRIF) affiliated with IAPR, and the "Groupe Français de l'Imagerie Numérique Couleur" (GFINC). The first CCIW was organized in 2007 in Modena, Italy, with the endorsement of IAPR. This workshop was held along with the International Conference on Image Analysis and Processing (ICIAP), the main conference on image processing and pattern recognition organized every two years by the Group of Italian Researchers on Pattern Recognition (GIRPR) affiliated with the International Association for Pattern Recognition (IAPR). Our first goal, since we began the planning of the workshop, was to bring together engineers and scientists from various imaging companies and from technical com- nities all over the world to discuss diverse aspects of their latest work, ranging from theoretical developments to practical applications in the field of color imaging, color image processing and analysis. The workshop was therefore intended for researchers and practitioners in the digital imaging, multimedia, visual communications, computer vision, and consumer electronic industry, who are interested in the fundamentals of color image processing and its emerging applications.
This book constitutes the refereed proceedings of the 7th Computational Color Imaging Workshop, CCIW 2019, held in Chiba, Japan, in March 2019. The 22 full papers presented in this volume were carefully reviewed and selected from 34 submissions. The papers are organized in topical sections named: computational color imaging; multispectral imaging; perceptual model and application; color image evaluation; colot image filtering; color image applications; and color imaging for material appearance. In addition, the book contains 3 invited talks in full paper length.
This book constitutes the refereed proceedings of the 6th Computational Color Imaging Workshop, CCIW 2017, held in Milano, Italy, in March 2017. The 23 full papers, including 4 tutorials and 3 invited papers, accepted were carefully reviewed and selected from 25 submissions. The papers are organized in topical sections on color image processing; color image quality; color in digital cultural heritage; spectral imaging; color characterization; color image analysis.
Henry Kang provides the fundamental color principles and mathematical tools to prepare the reader for a new era of color reproduction, and for subsequent applications in multispectral imaging, medical imaging, remote sensing, and machine vision. This book is intended to bridge the gap between color science and computational color technology, putting color adaptation, color constancy, color transforms, color display, and color rendition in the domain of vector-matrix representations and theories. Computational Color Technology deals with color digital images on the spectral level using vector-matrix representations so that the reader can learn to process digital color images via linear algebra and matrix theory.
Presenting a practical, problem-based approach to colour physics, this title describes the key issues encountered in modern colour engineering, including efficient representation of colour information, fourier analysis of reflectance spectra and advanced colorimetric computation. Emphasis is placed on the practical applications rather than the techniques themselves, with material structured around key topics, such as colour calibration of visual displays, computer recipe prediction and models for colour-appearance prediction. Each topic is carefully introduced at three levels to enhance student understanding. Firstly, theoretical ideas and background information are discussed, explanations of mathematical solutions then follow and finally practical solutions are presented using MATLAB. Includes a compendium of equations and numerical data required by the modern colour and imaging scientist. Numerous examples of solutions and algorithms for a wide-range of computational problems in colour science. Provides example scripts using the MATLAB programming language. This text is a must-have for students taking courses in colour science, colour chemistry and colour physics as well as technicians and researchers working in the area.
This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization with the goal of designing tractable algorithms. Throughout the handbook, the authors introduce topics on the most key aspects of image acquisition and processing that are based on the formulation and solution of novel optimization problems. The first part includes a review of the mathematical methods and foundations required, and covers topics in image quality optimization and assessment. The second part of the book discusses concepts in image formation and capture from color imaging to radar and multispectral imaging. The third part focuses on sparsity constrained optimization in image processing and vision and includes inverse problems such as image restoration and de-noising, image classification and recognition and learning-based problems pertinent to image understanding. Throughout, convex optimization techniques are shown to be a critically important mathematical tool for imaging science problems and applied extensively. Convex Optimization Methods in Imaging Science is the first book of its kind and will appeal to undergraduate and graduate students, industrial researchers and engineers and those generally interested in computational aspects of modern, real-world imaging and image processing problems.
Computational photography refers broadly to imaging techniques that enhance or extend the capabilities of digital photography. This new and rapidly developing research field has evolved from computer vision, image processing, computer graphics and applied optics—and numerous commercial products capitalizing on its principles have already appeared in diverse market applications, due to the gradual migration of computational algorithms from computers to imaging devices and software. Computational Photography: Methods and Applications provides a strong, fundamental understanding of theory and methods, and a foundation upon which to build solutions for many of today's most interesting and challenging computational imaging problems. Elucidating cutting-edge advances and applications in digital imaging, camera image processing, and computational photography, with a focus on related research challenges, this book: Describes single capture image fusion technology for consumer digital cameras Discusses the steps in a camera image processing pipeline, such as visual data compression, color correction and enhancement, denoising, demosaicking, super-resolution reconstruction, deblurring, and high dynamic range imaging Covers shadow detection for surveillance applications, camera-driven document rectification, bilateral filtering and its applications, and painterly rendering of digital images Presents machine-learning methods for automatic image colorization and digital face beautification Explores light field acquisition and processing, space-time light field rendering, and dynamic view synthesis with an array of cameras Because of the urgent challenges associated with emerging digital camera applications, image processing methods for computational photography are of paramount importance to research and development in the imaging community. Presenting the work of leading experts, and edited by a renowned authority in digital color imaging and camera image processing, this book considers the rapid developments in this area and addresses very particular research and application problems. It is ideal as a stand-alone professional reference for design and implementation of digital image and video processing tasks, and it can also be used to support graduate courses in computer vision, digital imaging, visual data processing, and computer graphics, among others.
Since the early 20th century, medical imaging has been dominated by monochrome imaging modalities such as x-ray, computed tomography, ultrasound, and magnetic resonance imaging. As a result, color information has been overlooked in medical image analysis applications. Recently, various medical imaging modalities that involve color information have been introduced. These include cervicography, dermoscopy, fundus photography, gastrointestinal endoscopy, microscopy, and wound photography. However, in comparison to monochrome images, the analysis of color images is a relatively unexplored area. The multivariate nature of color image data presents new challenges for researchers and practitioners as the numerous methods developed for monochrome images are often not directly applicable to multichannel images. The goal of this volume is to summarize the state-of-the-art in the utilization of color information in medical image analysis.
An explanation of colour technology for electronic imaging at the system level, including tools for colour image processing, tools for digital image processing that affect image quality, and applications.
