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This second edition of the Handbook of Image Engineering offers a thoroughly expanded and updated reference for the rapidly evolving field of image engineering. Building on the success of the first edition, which attracted more than 100,000 accesses, the new edition extends coverage from 10,000 to 15,000 entries, providing an even more comprehensive and well-structured knowledge base.
The handbook systematically integrates image processing, image analysis, image understanding, and applications, presenting concise definitions, principles, and explanations alongside practical techniques, illustrative examples, and advanced methodologies. Topics range from image acquisition, coding, enhancement, restoration, and security to segmentation, recognition, 3D reconstruction, spatiotemporal fusion, and deep learning. Critical challenges-such as high-precision image recovery and complex scene interpretation-are introduced with selected solutions, encouraging further exploration.
Designed for a broad professional readership, the volume serves multiple purposes:
A clear introduction for newcomers entering the field of image technology.
A concise summary for students consolidating their learning.
A practical reference for engineers addressing application-driven problems.
A comprehensive resource for researchers seeking advanced insights and interdisciplinary connections. With its authoritative coverage, refined organization, and accessible format, this handbook is an indispensable reference for academics, professionals, and practitioners engaged in computer vision, image engineering, and related disciplines.
This second edition of the Handbook of Image Engineering offers a thoroughly expanded and updated reference for the rapidly evolving field of image engineering. Building on the success of the first edition, which attracted more than 100,000 accesses, the new edition extends coverage from 10,000 to 15,000 entries, providing an even more comprehensive and well-structured knowledge base.
The handbook systematically integrates image processing, image analysis, image understanding, and applications, presenting concise definitions, principles, and explanations alongside practical techniques, illustrative examples, and advanced methodologies. Topics range from image acquisition, coding, enhancement, restoration, and security to segmentation, recognition, 3D reconstruction, spatiotemporal fusion, and deep learning. Critical challenges-such as high-precision image recovery and complex scene interpretation-are introduced with selected solutions, encouraging further exploration.
Designed for a broad professional readership, the volume serves multiple purposes:
A clear introduction for newcomers entering the field of image technology.
A concise summary for students consolidating their learning.
A practical reference for engineers addressing application-driven problems.
A comprehensive resource for researchers seeking advanced insights and interdisciplinary connections. With its authoritative coverage, refined organization, and accessible format, this handbook is an indispensable reference for academics, professionals, and practitioners engaged in computer vision, image engineering, and related disciplines.
Atsiliepimai