The book is written in clear terms so that readers from a wide range of disciplines with basic mathematical knowledge can use this text. Presenting the material at two levels, readers can use the direct text in order to gain a thorough understanding of the fundamentals of image processing, with advanced material contained within boxes interleaved throughout the text explaining the mathematical details of topics. The book covers basic topics of image processing such as image transformations, image enhancement, image restoration, edge detection and image segmentation, and image colour analysis. The most significant new material in the thoroughly revised and updated second edition of Image Processing: The Fundamentals includes an additional chapter on image processing andcolour, as well as several new sections on even and odd symmetric cosine transforms, and even and odd sine transforms, as well as a new section on Independent Component Analysis (ICA).Maria Petrou, Department of Electrical and Electronic Engineering, Imperial College London, London, UK Professor Maria Petrou has been teaching image processing for more than 20 years, within both academic and industry settings. As well as co-authoring the first edition of Image Processing: The Fundamentals (1999), Professor Petrou has also co-authored Imaging Processing: Dealing with Texture (2006), both published by Wiley. She has recently co-edited a book on the human visual system published in July 2008 by Artech House. Professor Petrou has also published more than 10 book chapters. Dr Costas Petrou, Independentsoftware consultant, Thessaloniki, Greece Dr Costas Petrou studied for his PhD in Electrical Engineering at UCL. He now works as an independent software consultant in Thessaloniki, Greece. INDICE: Preface. 1 Introduction. 2 Image Transformations. 2.1 Singular value decomposition. 2.2 Haar, Walsh and Hadamard transforms. 2.3 Discrete Fourier transform. 2.4 The even symmetric discrete cosine transform (EDCT). 2.5 The odd symmetric discrete cosine transform (ODCT). 2.6 The even antisymmetric discrete sine transform (EDST). 2.7 The odd antisymmetric discrete sine transform(ODST). 3 Statistical Description of Images. 3.1 Random fields. 3.2 Karhunen-Loeve transform. 3.3 Independent component analysis. 4 Image Enhancement. 4.1 Elements of linear filter theory. 4.2 Reducing high frequency noise. 4.3 Reducing low frequency interference. 4.4 Histogram manipulation. 4.5 Generic deblurring algorithms. 5 Image Restoration. 5.1 Homogeneous linear image restoration: inverse filtering. 5.2 Homogeneous linear image restoration: Wiener filtering. 5.3 Homogeneous linear image restoration: Constrained matrix inversion. 5.4Inhomogeneous linear image restoration: the whirl transform. 5.5 Nonlinear image restoration: MAP estimation. 5.6 Geometric image restoration. 6 Image Segmentation and Edge Detection. 6.1 Image segmentation. 6.2 Edge detection. 6.3 Phase congruency and the monogenic signal. 7 Image Processing for MultispectralImages. 7.1 Image preprocessing for multispectral images. 7.2 The physics andpsychophysics of colour vision. 7.3 Colour image processing in practice. Bibliographical notes. References. Index.
- ISBN: 978-0-470-74586-1
- Editorial: Wiley
- Encuadernacion: Cartoné
- Páginas: 824
- Fecha Publicación: 09/04/2010
- Nº Volúmenes: 1
- Idioma: Inglés