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This book offers readers an essential introduction to the fundamentals of digital image processing. Pursuing a signal processing and algorithmic approach, it makes the fundamentals of digital image processing accessible and easy to learn. It is written in a clear and concise manner with a large number of 4 x 4 and 8 x 8 examples, figures and detailed explanations. Each concept is developed from the basic principles and described in detail with equal emphasis on theory and practice. The book is accompanied by a companion website that provides several MATLAB programs for the implementation of image processing algorithms. The book also offers comprehensive coverage of the following topics: Enhancement, Transform processing, Restoration, Registration, Reconstruction from projections, Morphological image processing, Edge detection, Object representation and classification, Compression, and Color processing.

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Intro -- Preface -- About the Book -- Contents -- About the Author -- Abbreviations -- 1 Introduction -- 1.1 Image Acquisition -- 1.2 Digital Image -- 1.2.1 Representation in the Spatial Domain -- 1.2.2 Representation in the Frequency Domain -- 1.3 Quantization and Sampling -- 1.3.1 Quantization -- 1.3.2 Spatial Resolution -- 1.3.3 Sampling and Aliasing -- 1.3.4 Image Reconstruction and the Moiré Effect -- 1.4 Applications of Digital Image Processing -- 1.5 The Organization of This Book -- 1.6 Summary -- 2 Image Enhancement in the Spatial Domain -- 2.1 Point Operations -- 2.1.1 Image Complement -- 2.1.2 Gamma Correction -- 2.2 Histogram Processing -- 2.2.1 Contrast Stretching -- 2.2.2 Histogram Equalization -- 2.2.3 Histogram Specification -- 2.3 Thresholding -- 2.4 Neighborhood Operations -- 2.4.1 Linear Filtering -- 2.4.2 Median Filtering -- 2.5 Summary -- 3 Fourier Analysis -- 3.1 The 1-D Discrete Fourier Transform -- 3.2 The 2-D Discrete Fourier Transform -- 3.3 DFT Representation of Images -- 3.4 Computation of the 2-D DFT -- 3.5 Properties of the 2-D DFT -- 3.6 The 1-D Fourier Transform -- 3.7 The 2-D Fourier Transform -- 3.8 Summary -- 4 Image Enhancement in the Frequency Domain -- 4.1 1-D Linear Convolution Using the DFT -- 4.2 2-D Linear Convolution Using the DFT -- 4.3 Lowpass Filtering -- 4.3.1 The Averaging Lowpass Filter -- 4.3.2 The Gaussian Lowpass Filter -- 4.4 The Laplacian Filter -- 4.4.1 Amplitude and Phase Distortions -- 4.5 Frequency-Domain Filters -- 4.5.1 Ideal Filters -- 4.5.2 The Butterworth Lowpass Filter -- 4.5.3 The Butterworth Highpass Filter -- 4.5.4 The Gaussian Lowpass Filter -- 4.5.5 The Gaussian Highpass Filter -- 4.5.6 Bandpass and Bandreject Filtering -- 4.6 Homomorphic Filtering -- 4.7 Summary -- 5 Image Restoration -- 5.1 The Image Restoration Process -- 5.2 Inverse Filtering -- 5.3 Wiener Filter -- 5.3.1 The 2-D Wiener Filter -- 5.4 Image Degradation Model -- 5.5 Characterization of the Noise and Its Reduction -- 5.5.1 Uniform Noise -- 5.5.2 Gaussian Noise -- 5.5.3 Periodic Noise -- 5.5.4 Noise Reduction -- 5.6 Summary -- 6 Geometric Transformations and Image Registration -- 6.1 Interpolation -- 6.1.1 Nearest-Neighbor Interpolation -- 6.1.2 Bilinear Interpolation -- 6.2 Affine Transform -- 6.2.1 Scaling -- 6.2.2 Shear -- 6.2.3 Translation -- 6.2.4 Rotation -- 6.3 Correlation -- 6.3.1 1-D Correlation -- 6.3.2 2-D Correlation -- 6.4 Image Registration -- 6.5 Summary -- 7 Image Reconstruction from Projections -- 7.1 The Normal Form of a Line -- 7.2 The Radon Transform -- 7.2.1 Properties of the Radon Transform -- 7.2.2 The Discrete Approximation of the Radon Transform -- 7.2.3 The Fourier-Slice Theorem -- 7.2.4 Reconstruction with Filtered Back-projections -- 7.3 Hough Transform -- 7.4 Summary -- 8 Morphological Image Processing -- 8.1 Binary Morphological Operations -- 8.1.1 Dilation -- 8.1.2 Erosion -- 8.1.3 Opening and Closing -- 8.1.4 Hit-and-Miss Transformation -- 8.1.5 Morphological Filtering -- 8.2 Binary Morphological Algorithms -- 8.2.1 Thinning -- 8.2.2 Thickening -- 8.2.3 Noise Removal -- 8.2.4 Skeletons -- 8.2.5 Fill -- 8.2.6 Boundary Extraction -- 8.2.7 Region Filling -- 8.2.8 Extraction of Connected Components -- 8.2.9 Convex Hull -- 8.2.10 Pruning -- 8.3 Grayscale Morphology -- 8.3.1 Dilation -- 8.3.2 Erosion -- 8.3.3 Opening and Closing -- 8.3.4 Top-Hat and Bottom-Hat Transformations -- 8.3.5 Morphological Gradient -- 8.4 Summary -- 9 Edge Detection -- 9.1 Edge Detection -- 9.1.1 Edge Detection by Compass Gradient Operators -- 9.2 Canny Edge Detection Algorithm -- 9.3 Laplacian of Gaussian -- 9.4 Summary -- 10 Segmentation -- 10.1 Edge-Based Segmentation -- 10.1.1 Point Detection -- 10.1.2 Line Detection -- 10.2 Threshold-Based Segmentation -- 10.2.1 Thresholding by Otsu''s Method -- 10.3 Region-Based Segmentation -- 10.3.1 Region Growing -- 10.3.2 Region Splitting and Merging -- 10.4 Watershed Algorithm -- 10.4.1 The Distance Transform -- 10.4.2 The Watershed Algorithm -- 10.5 Summary -- 11 Object Description -- 11.1 Boundary Descriptors -- 11.1.1 Chain Codes -- 11.1.2 Signatures -- 11.1.3 Fourier Descriptors -- 11.2 Regional Descriptors -- 11.2.1 Geometrical Features -- 11.2.2 Moments -- 11.2.3 Textural Features -- 11.3 Principal Component Analysis -- 11.4 Summary -- 12 Object Classification -- 12.1 The k-Nearest Neighbors Classifier -- 12.2 The Minimum-Distance-to-Mean Classifier -- 12.2.1 Decision-Theoretic Methods -- 12.3 Decision Tree Classification -- 12.4 Bayesian Classification -- 12.5 k-Means Clustering -- 12.6 Summary -- 13 Image Compression -- 13.1 Lossless Compression -- 13.1.1 Huffman Coding -- 13.1.2 Run-Length Encoding -- 13.1.3 Lossless Predictive Coding -- 13.1.4 Arithmetic Coding -- 13.2 Transform-Domain Compression -- 13.2.1 The Discrete Wavelet Transform -- 13.2.2 Haar 2-D DWT -- 13.2.3 Image Compression with Haar Filters -- 13.3 Image Compression with Biorthogonal Filters -- 13.3.1 CDF 9/7 Filter -- 13.4 Summary -- 14 Color Image Processing -- 14.1 Color Models -- 14.1.1 The RGB Model -- 14.1.2 The XYZ Color Model -- 14.1.3 The CMY and CMYK Color Models -- 14.1.4 The HSI Color Model -- 14.1.5 The NTSC Color Model -- 14.1.6 The YCbCr Color Model -- 14.2 Pseudocoloring -- 14.2.1 Intensity Slicing -- 14.3 Color Image Processing -- 14.3.1 Image Complement -- 14.3.2 Contrast Enhancement -- 14.3.3 Lowpass Filtering -- 14.3.4 Highpass Filtering -- 14.3.5 Median Filtering -- 14.3.6 Edge Detection -- 14.3.7 Segmentation -- 14.4 Summary -- Appendix A Computation of the DFT -- A.1 The DFT Problem Formulation -- A.2 Half-Wave Symmetry of Periodic Waveforms -- A.3 The DFT and the Half-Wave Symmetry -- A.4 The PM DIF DFT Algorithm -- A.5 The PM DIT DFT Algorithm -- Bibliography -- Answers to Selected Exercises -- Index -- .