The Image Processing Handbook, Second Edition

From the reviews of the First Edition:

Table of Contents:
Acquiring Images Human Reliance on Images for Information Using Video Cameras to Acquire Images Electronics and Bandwidth Limitations High Resolution Imaging Color Imaging Color Displays Image Types Range Imaging Multiple Images Stereoscopy Imaging Requirements Printing and Storage Printing Dots On Paper Color Printing Printing Hardware Film Recorders File Storage Optical Storage Media Magnetic Recording Data Bases for Images Browsing and Thumbnails Lossless Coding Color Palettes Lossy Compression Other Compression Methods Digital Movies Correcting Image Defects Noisy Images Neighborhood Averaging Neighborhood Ranking Other Neighborhood Noise Reduction Methods Maximum Entropy Contrast Expansion Nonuniform Illumination Fitting a Background Function Rank Leveling Color Shading Non-Planar Views Computer Graphics Geometrical Distortion Alignment Morphing Image Enhancement Contrast Manipulation Histogram Equalization Laplacian Derivatives The Sobel and Kirsch Operators Rank Operations Texture Fractal Analysis Implementation Notes Image Math Subtracting Images Multiplication and Division Processing Images In Frequency Space Some Necessary Mathematical Preliminaries What Frequency Space Is All About The Fourier Transform Fourier Transforms of Real Functions Frequencies and Orientations Measuring Images in the Frequency Domain Orientation and Spacing Preferred Orientation Texture and Fractals Filtering Images Isolating Periodic Noise Masks and Filters Selection of Periodic Information Convolution and Correlation Fundamentals of Convolution Imaging System Characteristics Removing Motion Blur and Other Defects Template Matching and Correlation Autocorrelation Conclusion Segmentation and Thresholding Thresholding Multiband Images Two-Dimensional Thresholds Multiband Thresholding Thresholding from Texture Multiple Thresholding Criteria Textural Orientation Accuracy and Reproducibility Including Position Information Selective Histograms Boundary Lines Contours Image Representation Other Segmentation Methods The General Classification Problem Processing Binary Images Boolean Operations Combining Boolean Operations Masks From Pixels to Features Boolean Logic with Features Selecting Features by Location Double Thresholding Erosion and Dilation Opening and Closing Isotropy Measurements Using Erosion and Dilation Extension to Grey-Scale Images The Coefficient and Depth Parameters Examples of Use The Cluster Skeletonization Boundary Lines and Thickening Euclidian Distance Map Watershed Segmentation Ultimate Eroded Points Fractal Dimension Measurement Medial Axis Transform Cluster Analysis Image Measurements Brightness Measurements Determining Location Orientation Neighbor Relationships Alignment Counting Features Special Counting Procedures Feature Size Caliper Dimensions Perimeter Ellipse Fitting Describing Shape Fractal Dimension Harmonic Analysis Topology Feature Identification Three-Dimensional Measurements 3D Image Acquisition Volume Imaging vs. Sections Basics of Reconstruction Algebraic Reconstruction Methods Maximum Entropy Defects in Reconstructed Images Imaging Geometries Three-Dimensional Tomography High Resolution Tomography 3D Image Visualization Sources of 3D Data Serial Sections Optical Sectioning Sequential Removal Stereo 3D Data Sets Slicing the Data Set Arbitrary Section Planes The Use of Color Volumetric Display Stereo Viewing Special Display Hardware Ray Tracing Reflection Surfaces Multiply Connected Surfaces Image Processing in 3D Measurements on 3D Images Conclusion References Index