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Gain a firm understanding of image processing as you cover the major topics of the field using a balanced approach that progresses from simple explanations to more detailed descriptions within IMAGE PROCESSING AND ANALYSIS. This easy-to-follow, accessible book emphasizes a basic, fundamental understanding of the classic algorithms in the field while also highlighting recent research results. You can grasp the subtle tradeoffs among different approaches as well as understand them in context with the latest developments in the field. Numerous full-color illustrations and detailed pseudocode bridge the gap between mathematical equations underlying the important concepts and real-world application of those concepts. This understanding makes it easier for you to program your own implementations of these algorithms. In addition, consistent notation throughout this edition makes it easier to follow the various concepts.

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1. INTRODUCTION. Image processing and analysis. History and related fields. Sample applications. Image basics. Looking forward. Further reading. Problems. 2. FUNDAMENTALS OF IMAGING. Vision in nature. Image formation. Image acquisition. Other imaging modalities. A detailed look at electromagnetic radiation. Further reading. Problems. 3. POINT AND GEOMETRIC TRANSFORMATIONS. Simple geometric transformations. Graylevel transformations. Graylevel histograms. Multi-spectral transformations. Multi-image transformations. Change detection. Compositing. Interpolation. Warping. Further reading. Problems. 4. BINARY IMAGE PROCESSING. Morphological operations. Labeling regions. Computing distance in a digital image. Region properties. Skeletonization. Boundary representations. 5. SPATIAL-DOMAIN FILTERING. Convolution. Smoothing by convolving with a Gaussian. Computing the first derivative. Computing the second derivative. Nonlinear filters. Grayscale morphological operators. Further reading. Problems. 6. FREQUENCY-DOMAIN PROCESSING. Fourier transform. Discrete Fourier transform (DFT). Two-dimensional DFT. Frequency-domain filtering. Localizing frequencies in time. Discrete wavelet transform (DWT). Further reading. Problems. 7. EDGES AND FEATURES. Multiresolution processing. Edge detection. Approximating intensity edges with polylines. Feature detectors. Feature descriptors. Further reading. Problems. 8. COMPRESSION. Basics. Lossless compression. Lossy compression. Compression of videos. Further reading. Problems. 9. COLOR. Physics and psychology of color. Trichromacy. Designating colors. Linear color transformations. Color spaces. Further reading. Problems. 10. SEGMENTATION. Thresholding. Deformable models. Image segmentation. Graph-based methods. Further reading. Problems. 11. MODEL FITTING Fitting curves. Fitting point cloud models. Robustness to noise. Fitting multiple models. Further reading. Problems. 12. CLASSIFICATION. Fundamentals. Statistical pattern recognition. Generative methods. Discriminative methods. Further reading. Problems. 13. STEREO AND MOTION. Human stereopsis. Matching stereo images. Computing optical flow. Projective geometry. Camera calibration. Geometry of multiple views. Further reading. Problems.

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