Название: A Course on Digital Image Processing with MATLAB, Second Edition
Автор: P.K. Thiruvikraman
Издательство: IOP Publishing
Год: 2024
Страниц: 333
Язык: английский
Формат: pdf (true), epub
Размер: 47.5 MB

Digital imaging is now ubiquitous, from the smart phone in your pocket to state-of-the-art medical imaging and satellite imagery. Raw imaging data can be manipulated using computer algorithms to perform a range of functions from reducing noise to complex image analysis and pattern and object recognition. The result is that digital image processing has applications in almost all areas of science and engineering. Designed for a one semester course, the aim of this book is to concentrate on the principles and techniques of image processing. This second edition includes important updates to the first edition, as well as two entirely new chapters, making the book ideal for advanced students in physics and engineering.

Digital image processing has applications in almost all areas of science and engineering. Remote sensing and medical imaging are two areas where the techniques of image processing find wide application. While commercial packages are readily available to implement the techniques used in image processing, it is necessary for practitioners of this field to have a thorough understanding of the basic principles of image processing.

The aim of this book is to concentrate on the fundamental principles and techniques of image processing. A conscious attempt has been made to give an in-depth presentation of selected topics, rather than a comprehensive survey of the entire field. Implementation of the various image processing algorithms is an important step in learning the subject. The author has come to realise that using a package like MATLAB (which has an image processing toolbox) quickens the learning process. While programming in a language like C has certain advantages, it is a time consuming process. The beginner is likely to be mired in syntax errors and the complexities of the programming language. This leaves the student less time to understand the algorithm being used. Two separate chapters have been devoted to the MATLAB programming environment and the image processing toolbox. Implementation of image processing algorithms using MATLAB is also emphasised in other chapters wherever it is considered appropriate.

MATLAB is one of the most widely used software packages for the analysis and visualization of data in science and engineering. It is also well suited for implementing algorithms for image processing since it has a separate image processing toolbox. The image processing toolbox contains many built-in functions for implementing many of the algorithms we have discussed in this book.

MATLAB is a powerful tool for data analysis and visualization. In addition, it has a number of ‘toolboxes’ which facilitate its application in many fields. One of the toolboxes that is available with MATLAB is the Image Processing toolbox. The Image Processing toolbox consists of a large number of in-built functions that make it very easy for us to implement various algorithms used in image processing. However, while using the toolboxes, one should not get carried away and over-use the in-built functions. Relying too much on in-built functions will not help us to understand the details of various algorithms which we use. Understanding the details of each algorithm is very essential if we have to modify and make them more efficient. Writing our own programs (instead of using in-built functions) will also help us in situations where we cannot use MATLAB.

Since MATLAB is a high-level language whose commands have to be translated into lower level languages by the computer, MATLAB programs will not run as fast as programs written in languages like C. Therefore, it is not preferred for real-time applications. Also, MATLAB occupies up lot of space in the memory. With these disadvantages you might well ask whether we are better off using a language like C. While it is true that MATLAB has certain disadvantages, it has a number of advantages that has resulted in its widespread use in the field of image processing. Developing programs in MATLAB is much simpler than in languages like C. Even as simple a task as reading an image file and storing the pixel intensities in an image requires a very large program with hundreds of lines of code in C language.




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