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Andreas Koschan Digital Color Image Processing


An introduction to color in three-dimensional image processing and the emerging area of multi-spectral image processing The importance of color information in digital image processing is greater than ever. However, the transition from scalar to vector-valued image functions has not yet been generally covered in most textbooks. Now, Digital Color Image Processing fills this pressing need with a detailed introduction to this important topic. In four comprehensive sections, this book covers: The fundamentals and requirements for color image processing from a vector-valued viewpoint Techniques for preprocessing color images Three-dimensional scene analysis using color information, as well as the emerging area of multi-spectral imaging Applications of color image processing, presented via the examination of two case studies In addition to introducing readers to important new technologies in the field, Digital Color Image Processing also contains novel topics such as: techniques for improving three-dimensional reconstruction, three-dimensional computer vision, and emerging areas of safety and security applications in luggage inspection and video surveillance of high-security facilities. Complete with full-color illustrations and two applications chapters, Digital Color Image Processing is the only book that covers the breadth of the subject under one convenient cover. It is written at a level that is accessible for first- and second-year graduate students in electrical and computer engineering and computer science courses, and that is also appropriate for researchers who wish to extend their knowledge in the area of color image processing.

17600.65 RUR

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Theo Gevers Color in Computer Vision


While the field of computer vision drives many of today’s digital technologies and communication networks, the topic of color has emerged only recently in most computer vision applications. One of the most extensive works to date on color in computer vision, this book provides a complete set of tools for working with color in the field of image understanding. Based on the authors’ intense collaboration for more than a decade and drawing on the latest thinking in the field of computer science, the book integrates topics from color science and computer vision, clearly linking theories, techniques, machine learning, and applications. The fundamental basics, sample applications, and downloadable versions of the software and data sets are also included. Clear, thorough, and practical, Color in Computer Vision explains: Computer vision, including color-driven algorithms and quantitative results of various state-of-the-art methods Color science topics such as color systems, color reflection mechanisms, color invariance, and color constancy Digital image processing, including edge detection, feature extraction, image segmentation, and image transformations Signal processing techniques for the development of both image processing and machine learning Robotics and artificial intelligence, including such topics as supervised learning and classifiers for object and scene categorization Researchers and professionals in computer science, computer vision, color science, electrical engineering, and signal processing will learn how to implement color in computer vision applications and gain insight into future developments in this dynamic and expanding field.

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Marc Ebner Color Constancy


A human observer is able to recognize the color of objects irrespective of the light used to illuminate them. This is called color constancy. A digital camera uses a sensor to measure the reflected light, meaning that the measured color at each pixel varies according to the color of the illuminant. Therefore, the resulting colors may not be the same as the colors that were perceived by the observer. Obtaining color constant descriptors from image pixels is not only important for digital photography, but also valuable for computer vision, color-based automatic object recognition, and color image processing in general. This book provides a comprehensive introduction to the field of color constancy, describing all the major color constancy algorithms, as well as presenting cutting edge research in the area of color image processing. Beginning with an in-depth look at the human visual system, Ebner goes on to: examine the theory of color image formation, color reproduction and different color spaces; discuss algorithms for color constancy under both uniform and non-uniform illuminants; describe methods for shadow removal and shadow attenuation in digital images; evaluate the various algorithms for object recognition and color constancy and compare this to data obtained from experimental psychology; set out the different algorithms as pseudo code in an appendix at the end of the book. Color Constancy is an ideal reference for practising engineers, computer scientists and researchers working in the area of digital color image processing. It may also be useful for biologists or scientists in general who are interested in computational theories of the visual brain and bio-inspired engineering systems.

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Сканер с автоподатчиком Duplex Color Image Reader Unit-H1 (8002B003)


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Сканер с автоподатчиком Duplex Color Image Reader Unit-H1 (8002B003) Canon

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Группа авторов Digital Color


In this book the authors identify the basic concepts and recent advances in the acquisition, perception, coding and rendering of color. The fundamental aspects related to the science of colorimetry in relation to physiology (the human visual system) are addressed, as are constancy and color appearance. It also addresses the more technical aspects related to sensors and the color management screen. Particular attention is paid to the notion of color rendering in computer graphics. Beyond color, the authors also look at coding, compression, protection and quality of color images and videos. Individual chapters focus on the LMS specification, color constancy, color appearance models, rendering in synthetic image generation, image sensor technologies, image compression, and quality and secure color imaging. Ideal for researchers, engineers, Master’s and PhD students, Digital Color: Acquisition, Perception, Encoding and Rendering offers a state of the art on all the scientific and technical issues raised by the different stages of the digital color process – acquisition, analysis and processing. Contents 1. Colorimetry and Physiology – The LMS Specification, Françoise Viénot and Jean Le Rohellec. 2. Color Constancy, Jean-Christophe Burie, Majed Chambah and Sylvie Treuillet. 3. Color Appearance Models, Christine Fernandez-Maloigne and Alain Trémeau. 4. Rendering and Computer Graphics, Bernard Péroche, Samuel Delepoulle and Christophe Renaud. 5. Image Sensor Technology, François Berry and Omar Ait Aider. 6. From the Sensor to Color Images, Olivier Losson and Eric Dinet. 7. Color and Image Compression, Abdelhakim Saadane, Mohamed-Chaker Larabi and Christophe Charrier. 8. Protection of Color Images, William Puech, Alain Trémeau and Philippe Carré. 9. Quality Assessment Approaches, Mohamed-Chaker Larabi, Abdelhakim Saadane and Christophe Charrier.

14352.98 RUR

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Сканер с автоподатчиком Duplex Color Image Reader Unit-F1 (5780B003)


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Сканер с автоподатчиком Duplex Color Image Reader Unit-A1 (3689B003)


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Rangaraj Rangayyan M. Digital Image Processing for Ophthalmology

Anna L. Ells Digital Image Processing for Ophthalmology

Группа авторов Digital Color Imaging


This collective work identifies the latest developments in the field of the automatic processing and analysis of digital color images. For researchers and students, it represents a critical state of the art on the scientific issues raised by the various steps constituting the chain of color image processing. It covers a wide range of topics related to computational color imaging, including color filtering and segmentation, color texture characterization, color invariant for object recognition, color and motion analysis, as well as color image and video indexing and retrieval. Contents 1. Color Representation and Processing in Polar Color Spaces, Jesús Angulo, Sébastien Lefèvre and Olivier Lezoray. 2. Adaptive Median Color Filtering, Frédérique Robert-Inacio and Eric Dinet. 3. Anisotropic Diffusion PDEs for Regularization of Multichannel Images: Formalisms and Applications, David Tschumperlé. 4. Linear Prediction in Spaces with Separate Achromatic and Chromatic Information,Olivier Alata, Imtnan Qazi, Jean-Christophe Burie and Christine Fernandez-Maloigne. 5. Region Segmentation, Alain Clément, Laurent Busin, Olivier Lezoray and Ludovic Macaire. 6. Color Texture Attributes, Nicolas Vandenbroucke, Olivier Alata, Christèle Lecomte, Alice Porebski and Imtnan Qazi. 7. Photometric Color Invariants for Object Recognition, Damien Muselet. 8. Color Key Point Detectors and Local Color Descriptors, Damien Muselet and Xiaohu Song. 9. Motion Estimation in Color Image Sequences, Bertrand Augereau and Jenny Benois-Pineau.

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Tinku Acharya JPEG2000 Standard for Image Compression


JPEG2000 Standard for Image Compression presents readers with the basic background to this multimedia compression technique and prepares the reader for a detailed understanding of the JPEG2000 standard, using both the underlying theory and the principles behind the algorithms of the JPEG2000 standard for scalable image compression. It introduces the VLSI architectures and algorithms for implementation of the JPEG2000 standard in hardware (not available in the current literature), an important technology for a number of image processing applications and devices such as digital camera, color fax, printer, and scanners.

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Mandala Digital Nu Dop * color 2


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