Digital Image Processing and Image Acquisition

This textbook provides students and users with the necessary knowledge to successfullyto successfully acquire and process image data. It is consistently taken into account that image acquisition and image processing are based on the same mathematical concepts. Great emphasis was placed to present the sometimes complex relationships both clearly and mathematically sound.The material in the 7th edition of this textbook, which has been successful since 1991, has been restructured.In line with the rapid development of image sensor technology, optics and image sensor technology, optics and the diverse methods of reconstructing the three-dimensional world from image data. The focus was placed on working out the basic concepts. This enables the reader tounderstand the initially confusing variety of image acquisition methods and learn how to use them optimally. Artificial intelligence methods have deliberately not been integrated into the book. Rather, this book contains the necessary knowledge about image acquisition and processing in order to apply machine learning methods to image analysis in the best possible way.

Uses examples and images to illustrate basic concepts Standard Textbook of Digital Image Processing A systematic approach to digital image processing and image formation

Autorentext
Bernd Jähne is senior professor at the Interdisciplinary Center for Scientific Computing (IWR) and the Institute of Environmental Physics (IUP) of Heidelberg University. From 2008 to 2017 he was coordinating director of the Heidelberg Collaboratory for Image processing (HCI), an industry-on-campus project of Heidelberg University and from 2008 to 2016 deputy director of the IWR. He is also founder and chair of the Heidelberg Image Processing Forum since 1995, chair of the EMVA 1288 standardization group since 2008, and vice president of the European Machine Vision Association from 2021 -2024. He is author of a several text books and handbooks on Digital Image Processing and Computer Vision published in German, English, and Russian language.

Klappentext

This textbook provides students and users with the knowledge necessary to successfully acquire and process image data. The fact that image acquisition and image processing are based on similar mathematical concepts is recognized throughout. Great emphasis has been placed on presenting the sometimes complex relationships in a descriptive and mathematically sound manner.

This 7th edition of the successful textbook, first published in 1991, has been restructured. The section on image acquisition has been significantly expanded to reflect the rapid developments in image sensor technology, optics, and methods for reconstructing three-dimensional worlds from image data. The emphasis is on explaining the basic concepts so that readers can understand and learn to optimize the variety of image acquisition methods that may seem confusing at first.

Artificial intelligence methods are not included in this book. Instead, this book provides the necessary knowledge about image acquisition and processing to apply machine learning methods to image analysis effectively.

The Author

Bernd Jähne is senior professor at the Interdisciplinary Center for Scientific Computing (IWR) and the Institute of Environmental Physics (IUP) of Heidelberg University. From 2008 to 2017 he was coordinating director of the Heidelberg Collaboratory for Image processing (HCI), an industry-on-campus project of Heidelberg University and from 2008 to 2016 deputy director of the IWR. He is also founder and chair of the Heidelberg Image Processing Forum since 1995, chair of the EMVA 1288 standardization group since 2008, and was vice president of the European Machine Vision Association from 2021 -2024. He is author of a several text books and handbooks on Digital Image Processing and Computer Vision published in German, English, and Russian language.

Inhalt

Introduction.- IMAGE FORMATION: Radiation and Quantitative Image Formation.- 2-D Image Acquisition.- Radiation Detection and Image Sensors.- Sampling and Interpolation.- Discrete Image Representation.- Radiometric and Geometric Image Correction.- 3-D Image Acquisition and Light Fields.- 3-D Imaging with Active Illumination.- IMAGE PROCESSING: Neighborhood Operators and Local Structure.- Averaging and Noise Suppression.- Discontinuities: Edges, Lines, Surfaces, and Corners.- Local Orientation, Local Wave Number and Phase.- Motion.- Scale Spaces and Multigrid Structures.- Textur and Complex Features.- Regularization and Modeling.- Morphology and Form Analysis.- MATHEMATICAL FOUNDATION AND REFERENCE MATERIAL: Notation.- Vector Spaces and Unitary Transforms.- Statistics, Regression and Optimization.- Reference Material.