Signal processing and image processing for acoustical imaging /

Signal processing and image processing for acoustical imaging /

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Bibliographic Details
Author / Creator:Gan, Woon Siong, author.
Imprint:Singapore : Springer, [2020]
©2020
Description:1 online resource (87 pages) : illustrations (some color)
Language:English
Subject:
Acoustic imaging.
Signal processing -- Digital techniques.
Acoustic imaging.
Signal processing -- Digital techniques.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12604778
Hidden Bibliographic Details
ISBN:9789811055508
9811055505
9789811055492
Notes:Description based upon print version of record.
11.5.1 Theory of the Fourier Transform
Contains bibliographical references.
Summary:This book discusses the applications of signal and image processing in acoustical imaging. It first describes the basic tools involved - the 2D transform, fast Fourier transform (FFT) and applications, and deconvolution - before introducing readers to higher-order statistics, wavelets, and neural networks. It also addresses the important topic of digital signal processing, focusing on the example of homomorphic signal processing. The book then details the design of digital filters and array signal processing, and lastly examines applications in image processing: image enhancement and optimization, image restoration, and image compression.
Other form:Print version: Gan, Woon Siong Signal Processing and Image Processing for Acoustical Imaging Singapore : Springer Singapore Pte. Limited,c2020 9789811055492
Standard no.:10.1007/978-981-10-5
Table of Contents:
  • Intro
  • Preface
  • Contents
  • 1 What is Signal?
  • 1.1 Introduction
  • 1.2 Forms of Signals
  • 1.3 Information Theory
  • References
  • 2 Fourier Series
  • 2.1 Fourier Analysis
  • 2.2 Harmonic Analysis
  • 2.3 Properties of the Fourier Series
  • 2.4 Fourier Coefficients
  • 2.5 The Trigonometric Series and the Exponential Series are Equivalent
  • Reference
  • 3 Fourier Transform
  • 3.1 The Representation of the Fourier Transform
  • 3.2 The Definition of Fourier Transform
  • References
  • 4 Discrete Fourier Transform
  • Reference
  • 5 Fast Fourier Transform
  • 5.1 Introduction to Fast Fourier Transform
  • 5.2 The Definition of Fast Fourier Transform
  • 5.3 Fast Fourier Transform Algorithms
  • References
  • 6 Convolution, Correlation, and Power Spectral Density
  • 6.1 Introduction to Convolution
  • 6.2 Definition of Convolution
  • 6.3 Applications of Convolution
  • 6.4 Correlation Function
  • 6.5 Autocorrelation
  • 6.5.1 Autocorrelation of Continuous Time Signal
  • 6.5.2 Symmetry Property of the Autocorrelation Function
  • 6.5.3 Applications of Autocorrelation
  • 6.6 Cross Correlation
  • 6.6.1 Some Properties of Cross Correlation
  • 6.7 Power Spectral Density
  • 6.7.1 Applications of Power Spectral Density
  • Reference
  • 7 Wiener Filter and Kalman Filter
  • 7.1 Introduction
  • 7.2 Principle of the Wiener Filter
  • 7.3 Applications
  • 7.4 Kalman Filter-Introduction
  • 7.5 The Algorithm of the Kalman Filter
  • References
  • 8 Higher Order Statistics
  • 8.1 Introduction
  • Reference
  • 9 Digital Signal Processing
  • 9.1 Introduction
  • 9.2 Signal Sampling
  • 9.3 Domains of Digital Signal Processing
  • 9.3.1 Time Domain
  • 9.3.2 Frequency Domain
  • 9.4 Useful Tools in Digital Signal Processing
  • 9.4.1 Wavelet Transform
  • 9.4.2 Z-Transform
  • 9.5 The Implementation of Digital Signal Processing
  • 9.6 Applications of Digital Signal Processing
  • 9.7 Digital Signal Processor
  • 9.7.1 Architecture of a Digital Signal Processor
  • Reference
  • 10 Digital Image Processing
  • 10.1 Background
  • 10.2 Scope of Work
  • 10.3 Some Procedures of Digital Image Transformations
  • 10.3.1 Image Filtering
  • 10.4 Types of Digital Images
  • 10.4.1 Binary Image
  • 10.4.2 Black and White Image
  • 10.4.3 8 Bit Colour Format
  • 10.4.4 16 Bit Colour Format
  • 10.5 Image as a Matrix
  • 10.6 Scope of Image Processing
  • 10.6.1 Acquisition
  • 10.6.2 Image Enhancement
  • 10.6.3 Image Restoration
  • 10.6.4 Colour Image Processing
  • 10.6.5 Wavelets and Multi-resolution Processing
  • 10.6.6 Image Compression
  • 10.6.7 Morphological Processing
  • 10.6.8 Segmentation Procedure
  • 10.6.9 Representation and Description
  • 10.7 Key Stages in Digital Image Processing
  • Reference
  • 11 Digital Image Filtering
  • 11.1 Digital Filtering
  • 11.2 Convolution
  • 11.3 Application of Digital Filters in Digital Image Processing
  • 11.4 Digital Linear Filter in the Spatial Domain
  • 11.5 Digital Linear Filter in the Frequency Domain

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