Advanced digital imaging laboratory using MATLAB® /

Bibliographic Details
Main Author:	I︠A︡roslavskiĭ, L. P. (Leonid Pinkhusovich) (Author)
Format:	eBook
Language:	English
Published:	Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : IOP Publishing, [2014]
Series:	IOP expanding physics.
Subjects:	MATLAB. Image processing > Digital techniques. Three-dimensional imaging. Numerical analysis > Computer programs. Image processing. COMPUTERS / Image Processing.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

Preface
Author biography
Introduction
General remarks about the book
Instructions for readers
Image digitization
Introduction
Image discretization
Signal scalar quantization
Image compression
Digital image formation and computational imaging
Introduction
Image recovery from sparse irregularly sampled data. Recovery of images with occlusions
Numerical reconstruction of holograms
Image reconstruction from projections
Questions for self-testing
Image resampling and building continuous image models
Introduction
Signal/image subsampling through fractional shifts
Image resampling using 'continuous' image models
The three-step rotation algorithm
Comparison of image resampling methods
Comparison of signal numerical differentiation and integration methods
Questions for self-testing
Image and noise statistical characterization and diagnostics
Introduction
Image histograms
Image local moments and order statistics
Pixel attributes and neighborhoods
Image autocorrelation functions and power spectra
Image noise
Empirical diagnostics of image noise
Questions for self-testing
Statistical image models and pattern formation
Introduction
PWN models
LF models
PWN&LF and LF&PWN models
Evolutionary models
Questions for self-testing
Image correlators for detection and localization of objects
Introduction
Localization of a target on images contaminated with additive uncorrelated Gaussian noise. Normal and anomalous localization errors
'Matched filter' correlator versus signal-to-clutter ratio optimal correlator and local versus global signal-to-clutter ratio optimal correlators
Object localization and image edges
Questions for self-testing
Methods of image perfecting
Introduction
Correcting imaging system transfer functions
Filtering periodical interferences. Filtering 'banding' noise
'Ideal' and empirical Wiener filtering for image denoising and deblurring
Local adaptive filtering for image denoising
Filtering impulsive noise using linear filters
Image denoising using nonlinear (rank) filters
Questions for self-testing
Methods of image enhancement
Introduction
Contrast enhancement
Edge extraction. Max-Min and Size-EV methods
Questions for self-testing.