Image Processing: The Fundamentals (Hardcover, 2, Revised)

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.

5.4 Inhomogeneous 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 Multispectral Images.

7.1 Image preprocessing for multispectral images.

7.2 The physics and psychophysics of colour vision.

7.3 Colour image processing in practice.

Bibliographical notes.

References.

Index.