Digital Image Processing

1. Introduction What Is Digital Image Processing? The Origins of Digital Image Processing Examples of Fields that Use Digital Image Processing Fundamental Steps in Digital Image Processing Components of an Image Processing System 2. Digital Image Fundamentals Elements of Visual Perception Light and the Electromagnetic Spectrum. Image Sensing and Acquisition Image Sampling and Quantization Some Basic Relationships Between Pixels An Introduction to the Mathematical Tools Used in Digital Image Processing 3. Intensity Transformations and Spatial Filtering Background Some Basic Intensity Transformation Functions Histogram Processing. Fundamentals of Spatial Filtering Smoothing Spatial Filters Sharpening Spatial Filters Combining Spatial Enhancement Methods Using Fuzzy Techniques for Intensity Transformations and Spatial Filtering 4. Filtering in the Frequency Domain Background Preliminary Concepts Sampling and the Fourier Transform of Sampled Functions The Discrete Fourier Transform (DFT) of One Variable Extension to Functions of Two Variables Some Properties of the 2-D Discrete Fourier Transform The Basics of Filtering in the Frequency Domain Image Smoothing Using Frequency Domain Filters Image Sharpening Using Frequency Domain Filters Selective Filtering Implementation 5. Image Restoration and Reconstruction A Model of the Image Degradation/Restoration Process Noise Models Restoration in the Presence of Noise Only-Spatial Filtering Periodic Noise Reduction by Frequency Domain Filtering Linear, Position-Invariant Degradations. Estimating the Degradation Function Inverse Filtering Minimum Mean Square Error (Wiener) Filtering Constrained Least Squares Filtering. Geometric Mean Filter Image Reconstruction from Projections. 6. Color Image Processing Color Fundamentals Color Models Pseudocolor Image Processing Basics of Full-Color Image Processing Color Transformations. Smoothing and Sharpening Image Segmentation Based on Color Noise in Color Images Color Image Compression 7. Wavelets and Multiresolution Processing Background Multiresolution Expansions Wavelet Transforms in One Dimension The Fast Wavelet Transform Wavelet Transforms in Two Dimensions Wavelet Packets 8. Image Compression Fundamentals Some Basic Compression Methods Digital Image Watermarking 9. Morphological Image Processing Preliminaries Erosion and Dilation Opening and Closing The Hit-or-Miss Transformation Some Basic Morphological Algorithms Gray-Scale Morphology 10. Image Segmentation Fundamentals Point, Line, and Edge Detection Thresholding. Region-Based Segmentation Segmentation Using Morphological Watersheds The Use of Motion in Segmentation 11. Representation and Description Representation Boundary Descriptors Regional Descriptors Use of Principal Components for Description Relational Descriptors 12. Object Recognition Patterns and Pattern Classes Recognition Based on Decision-Theoretic Methods Structural Methods