The Image Processing Handbook

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