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How to Optimally Sample and Resample Images: Theory and Methods Using MATLABНазвание: How to Optimally Sample and Resample Images: Theory and Methods Using MATLAB
Автор: Leonid Yaroslavsky
Издательство: Bentham Science Publishers
Год: 2021
Страниц: 183
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

How to Optimally Sample and Resample Images: Theory and Methods Using MATLAB provides updated formulations of image sampling theory and practical algorithms of image sampling with sampling rates close to the theoretical minimum, and also introduces interpolation error-free methods of image resampling. Readers will be informed about relevant principles and applications of image sampling with the help of MATLAB. The information presented in the book, across 9 chapters, will help readers to understand processes that make analog to digital signal conversion efficient for modern imaging devices.

Key Features:

- Introduces readers to classical sampling theorems- Presents updated information about image sampling and resampling formulations with reference to theoretical minimums
- Presents information on practical and fast sampling algorithms
- Presents information about interpolation error-free methods of image resampling
- Presents examples of applications of the described methods
- Is supplemented by a MATLAB program package for exercising knowledge.

Digital imaging and image processing are among the major components of modern information technologies. Their very fundamental operation is a conversion of analog signals of image sensors into digital signals, i.e., into arrays of numbers that are stored and processed in the memory of digital cameras and computers, transmitted via digital communication channels and used for recreating images in display devices. This conversion is implemented through image sampling, i.e., by taking, in one or another way, signal samples at certain positions throughout the image area.

The book is a suitable handbook for engineers and technicians involved in imaging engineering and related applications as well as engineering students learning about digital signal processing techniques.

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