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Digital Holography and Digital Image Processing : Principles, Methods, Algorithms - Leonid Yaroslavsky

Digital Holography and Digital Image Processing

Principles, Methods, Algorithms

Hardcover Published: 30th November 2003
ISBN: 9781402076343
Number Of Pages: 584

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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 filters for sensor signal perfecting and image restoration and enhancement. The book combines theory, heavily illustrated practical methods and efficient computational algorithms and is written for senior-level undergraduate and graduate students, researchers and engineers in optics, photonics, opto-electronics and electronic engineering.

Introductionp. 1
Digital Holography and Evolution of Imaging Techniquesp. 1
Contents of this Bookp. 5
Optical Signals and Transformsp. 11
Mathematical Models of Optical Signalsp. 11
Signal Transformationsp. 24
Imaging Systems and Integral Transformsp. 27
Fourier Transform and its Derivativesp. 39
Imaging from Projections: Radon and Abel Transformsp. 57
Multi Resolution Imaging: Wavelet Transformsp. 61
Sliding Window Transforms and "Time-Frequency" (Space-Transform) Signal Representationp. 63
Stochastic Transformations and Statistical Modelsp. 67
Digital Representation of Signalsp. 79
Principles of Signal Digitizationp. 79
Signal Discretization as Expansion Over a Set of Basis Functions. Typical Basis Functions and Classificationp. 80
Shift (Convolution) Bases Functions and Sampling Theoremp. 106
Multi-Resolution Samplingp. 129
Unconventional Digital Imaging Methodsp. 131
Principles of Signal Scalar Quantizationp. 133
Basics of Signal Coding and Data Compressionp. 147
Digital Representation of Signal Transformationsp. 161
The Principlesp. 161
Discrete Representation of Convolution Integral. Digital Filtersp. 170
Discrete Representation of Fourier Integral Transformp. 170
Discrete Representation of Fresnel Integral Transformp. 199
Methods and Algorithms of Digital Filteringp. 211
Filtering in Signal Domainp. 211
Filtering in Transform Domainp. 226
Combined Algorithms for Computing DFT and DCT of Real Valued Signalsp. 231
Fast Algorithmsp. 239
The Principle of Fast Fourier Transformsp. 239
Matrix Techniques in Fast Transformsp. 243
Transforms and their Fast Algorithms in Matrix Representationp. 249
Pruned Algorithmsp. 264
Quantized DFTp. 269
Statistical Methods and Algorithmsp. 275
Measuring Signal Statistical Characteristicsp. 275
Digital Statistical Models and Monte Carlo Methodsp. 291
Statistical (Monte Carlo) Simulation. Case Study: Speckle Noise Phenomena in Coherent Imaging and Digital Holographyp. 305
Sensor Signal Perfecting, Image Restoration, Reconstruction and Enhancementp. 313
Mathematical Models of Imaging Systemsp. 313
Linear Filters for Image Restorationp. 315
Sliding Window Transform Domain Adaptive Signal Restorationp. 328
Multi-Component Image Restorationp. 340
Filtering Impulse Noisep. 343
Methods for Correcting Gray Scale Nonlinear Distortionsp. 348
Image Reconstructionp. 353
Image Enhancementp. 361
Image Resampling and Geometrical Transformationsp. 373
Principles of Image Resamplingp. 373
Nearest Neighbor, Linear and Spline Interpolation Methodsp. 376
Algorithms of Discrete Sinc-Interpolationp. 380
Application examplesp. 395
Signal Parameter Estimation and Measurement. Object Localizationp. 411
Problem Formulation. Optimal Statistical Estimatesp. 411
Localization of an Object in the Presence of Additive White Gaussian Noisep. 414
Performance of the Optimal Localization Devicep. 421
Localization of an Object in the Presence of Additive Correlated Gaussian Noisep. 443
Optimal Localization in Color and Multi Component Imagesp. 449
Object Localization in the Presence of Multiple Nonoverlappning Non-Target Objectsp. 454
Target Location in Clutterp. 461
Problem Formulationp. 461
Localization of Precisely Known Objects: Spatially Homogeneous Optimality Criterionp. 465
Localization of Inexactly Known Object: Spatially Homogeneous Criterionp. 474
Localization Methods for Spatially Inhomogeneous Criteriap. 478
Object Localization and Image Blurp. 483
Object Localization and Edge Detection. Selection of Reference Objects for Target Trackingp. 485
Optimal Adaptive Correlator and Optical Correlatorsp. 490
Target Locating in Color and Multi Component Imagesp. 499
Nonlinear Filters in Signal/Image Processingp. 509
Classification Principlesp. 510
Filter Classification Tablesp. 519
Practical Examplesp. 527
Computer Generated Hologramsp. 541
Mathematical Modelsp. 541
Methods for Encoding and Recording Computer Generated Hologramsp. 548
Reconstruction of Computer Generated Hologramsp. 565
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9781402076343
ISBN-10: 1402076347
Audience: Tertiary; University or College
Format: Hardcover
Language: English
Number Of Pages: 584
Published: 30th November 2003
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 23.5 x 15.5  x 3.81
Weight (kg): 2.25