Digital Picture Processing
Autor: | Azriel Rosenfeld |
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EAN: | 9780323148269 |
eBook Format: | |
Sprache: | Englisch |
Produktart: | eBook |
Veröffentlichungsdatum: | 01.01.1976 |
Kategorie: | |
Schlagworte: | compression computer digitization enhancement photograph restoration visual perception |
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Digital Picture Processing is a technique-oriented book aiming to teach the more extensive treatments of digital pictures. The book discusses picture processing; the computer representation of pictures; and the mathematical preliminaries involved. The visual perception, the digitization and the different techniques on sampling, and different techniques on compression are also covered. The book also explains the enhancement techniques, such as sharpening and moothing; filtering techniques used in restoration; and the geometry and description of a picture. The text is recommended to students of electrical engineering and computer science, who intend to learn better techniques in picture processing through digital means. The book is also suitable as an advanced undergraduate or a graduate course in picture processing.
The late Azriel Rosenfeld was a tenured research professor, a distinguished university professor, and the Founding Director of the Center for Automation Research at the University of Maryland in College Park, where he also held affiliate professorships in the departments of computer science, electrical engineering, and psychology. Dr. Rosenfeld was widely regarded as the leading researcher in the world in the field of computer image analysis. Over a period of nearly 40 years, he made fundamental and pioneering contributions to nearly every area of that field. He wrote the first textbook in the field, was founding editor of its first journal, and was co-chairman of its first international conference. He published over 30 books and over 600 book chapters and journal articles, and directed nearly 60 Ph.D. dissertations. Dr. Rosenfeld's research on digital image analysis—specifically on digital geometry and topology and the accurate measurement of statistical features of digital images in the 1960s and 1970s—formed the foundation for a generation of industrial vision inspection systems that have found widespread applications from the automotive to the electronics industry. He was a Fellow of the IEEE and the Washington Academy of Sciences; a Founding Fellow of the AAAI, the ACM, and the IAPR. Among his numerous awards and honors are the IEEE's Emanuel Piore Award, its Third Millennium Medal, and its Distinguished Service Award for Lifetime Achievement in Computer Vision and Pattern Recognition.
The late Azriel Rosenfeld was a tenured research professor, a distinguished university professor, and the Founding Director of the Center for Automation Research at the University of Maryland in College Park, where he also held affiliate professorships in the departments of computer science, electrical engineering, and psychology. Dr. Rosenfeld was widely regarded as the leading researcher in the world in the field of computer image analysis. Over a period of nearly 40 years, he made fundamental and pioneering contributions to nearly every area of that field. He wrote the first textbook in the field, was founding editor of its first journal, and was co-chairman of its first international conference. He published over 30 books and over 600 book chapters and journal articles, and directed nearly 60 Ph.D. dissertations. Dr. Rosenfeld's research on digital image analysis—specifically on digital geometry and topology and the accurate measurement of statistical features of digital images in the 1960s and 1970s—formed the foundation for a generation of industrial vision inspection systems that have found widespread applications from the automotive to the electronics industry. He was a Fellow of the IEEE and the Washington Academy of Sciences; a Founding Fellow of the AAAI, the ACM, and the IAPR. Among his numerous awards and honors are the IEEE's Emanuel Piore Award, its Third Millennium Medal, and its Distinguished Service Award for Lifetime Achievement in Computer Vision and Pattern Recognition.