Skip to content

Digital Holography and Digital Image Processing Principles, Methods, Algorithms

Spend $50 to get a free movie!

ISBN-10: 1402076347

ISBN-13: 9781402076343

Edition: 2004

Authors: Leonid Yaroslavsky

List price: $225.00
Blue ribbon 30 day, 100% satisfaction guarantee!
Out of stock
what's this?
Rush Rewards U
Members Receive:
Carrot Coin icon
XP icon
You have reached 400 XP and carrot coins. That is the daily max!


Digital holography and digital image processing are twins born by computer era. They share origin, theoretical base, methods and algorithms. The present book describes these common fundamentals principles, methods and algorithms including image and hologram digitization, data compression, digital transforms and efficient computational algorithms, statistical and Monte-Carlo methods, image restoration and enhancement, image reconstruction in tomography and digital holography, discrete signal resampling and image geometrical transformations, accurate measurements and reliable target localization in images, recording and reconstruction of computer generated holograms, adaptive and nonlinear…    
Customers also bought

Book details

List price: $225.00
Copyright year: 2004
Publisher: Springer
Publication date: 11/30/2003
Binding: Hardcover
Pages: 584
Size: 6.50" wide x 9.25" long x 1.50" tall
Weight: 2.090
Language: English

Digital Holography and Evolution of Imaging Techniques
Contents of this Book
Optical Signals and Transforms
Mathematical Models of Optical Signals
Signal Transformations
Imaging Systems and Integral Transforms
Fourier Transform and its Derivatives
Imaging from Projections: Radon and Abel Transforms
Multi Resolution Imaging: Wavelet Transforms
Sliding Window Transforms and "Time-Frequency" (Space-Transform) Signal Representation
Stochastic Transformations and Statistical Models
Digital Representation of Signals
Principles of Signal Digitization
Signal Discretization as Expansion Over a Set of Basis Functions. Typical Basis Functions and Classification
Shift (Convolution) Bases Functions and Sampling Theorem
Multi-Resolution Sampling
Unconventional Digital Imaging Methods
Principles of Signal Scalar Quantization
Basics of Signal Coding and Data Compression
Digital Representation of Signal Transformations
The Principles
Discrete Representation of Convolution Integral. Digital Filters
Discrete Representation of Fourier Integral Transform
Discrete Representation of Fresnel Integral Transform
Methods and Algorithms of Digital Filtering
Filtering in Signal Domain
Filtering in Transform Domain
Combined Algorithms for Computing DFT and DCT of Real Valued Signals
Fast Algorithms
The Principle of Fast Fourier Transforms
Matrix Techniques in Fast Transforms
Transforms and their Fast Algorithms in Matrix Representation
Pruned Algorithms
Quantized DFT
Statistical Methods and Algorithms
Measuring Signal Statistical Characteristics
Digital Statistical Models and Monte Carlo Methods
Statistical (Monte Carlo) Simulation. Case Study: Speckle Noise Phenomena in Coherent Imaging and Digital Holography
Sensor Signal Perfecting, Image Restoration, Reconstruction and Enhancement
Mathematical Models of Imaging Systems
Linear Filters for Image Restoration
Sliding Window Transform Domain Adaptive Signal Restoration
Multi-Component Image Restoration
Filtering Impulse Noise
Methods for Correcting Gray Scale Nonlinear Distortions
Image Reconstruction
Image Enhancement
Image Resampling and Geometrical Transformations
Principles of Image Resampling
Nearest Neighbor, Linear and Spline Interpolation Methods
Algorithms of Discrete Sinc-Interpolation
Application examples
Signal Parameter Estimation and Measurement. Object Localization
Problem Formulation. Optimal Statistical Estimates
Localization of an Object in the Presence of Additive White Gaussian Noise
Performance of the Optimal Localization Device
Localization of an Object in the Presence of Additive Correlated Gaussian Noise
Optimal Localization in Color and Multi Component Images
Object Localization in the Presence of Multiple Nonoverlappning Non-Target Objects
Target Location in Clutter
Problem Formulation
Localization of Precisely Known Objects: Spatially Homogeneous Optimality Criterion
Localization of Inexactly Known Object: Spatially Homogeneous Criterion
Localization Methods for Spatially Inhomogeneous Criteria
Object Localization and Image Blur
Object Localization and Edge Detection. Selection of Reference Objects for Target Tracking
Optimal Adaptive Correlator and Optical Correlators
Target Locating in Color and Multi Component Images
Nonlinear Filters in Signal/Image Processing
Classification Principles
Filter Classification Tables
Practical Examples
Computer Generated Holograms
Mathematical Models
Methods for Encoding and Recording Computer Generated Holograms
Reconstruction of Computer Generated Holograms