Discrete Fourier Analysis and Wavelets Applications to Signal and Image Processing 2nd Edition by S Allen Broughton, Kurt Bryan ISBN 1119258243 9781119258247

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Product details:

ISBN 10: 1119258243
ISBN 13:  9781119258247
Author: S Allen Broughton, Kurt Bryan

Delivers an appropriate mix of theory and applications to help readers understand the process and problems of image and signal analysis

Maintaining a comprehensive and accessible treatment of the concepts, methods, and applications of signal and image data transformation, this Second Edition of Discrete Fourier Analysis and Wavelets: Applications to Signal and Image Processing features updated and revised coverage throughout with an emphasis on key and recent developments in the field of signal and image processing. Topical coverage includes: vector spaces, signals, and images; the discrete Fourier transform; the discrete cosine transform; convolution and filtering; windowing and localization; spectrograms; frames; filter banks; lifting schemes; and wavelets.

Discrete Fourier Analysis and Wavelets introduces a new chapter on frames—a new technology in which signals, images, and other data are redundantly measured. This redundancy allows for more sophisticated signal analysis. The new coverage also expands upon the discussion on spectrograms using a frames approach. In addition, the book includes a new chapter on lifting schemes for wavelets and provides a variation on the original low-pass/high-pass filter bank approach to the design and implementation of wavelets. These new chapters also include appropriate exercises and MATLAB® projects for further experimentation and practice.

• Features updated and revised content throughout, continues to emphasize discrete and digital methods, and utilizes MATLAB® to illustrate these concepts
• Contains two new chapters on frames and lifting schemes, which take into account crucial new advances in the field of signal and image processing
• Expands the discussion on spectrograms using a frames approach, which is an ideal method for reconstructing signals after information has been lost or corrupted (packet erasure)
• Maintains a comprehensive treatment of linear signal processing for audio and image signals with a well-balanced and accessible selection of topics that appeal to a diverse audience within mathematics and engineering
• Focuses on the underlying mathematics, especially the concepts of finite-dimensional vector spaces and matrix methods, and provides a rigorous model for signals and images based on vector spaces and linear algebra methods
• Supplemented with a companion website containing solution sets and software exploration support for MATLAB and SciPy (Scientific Python)

Thoroughly class-tested over the past fifteen years, Discrete Fourier Analysis and Wavelets: Applications to Signal and Image Processing is an appropriately self-contained book ideal for a one-semester course on the subject.

Discrete Fourier Analysis and Wavelets Applications to Signal and Image Processing 2nd Table of contents:

1. Introduction to Signal and Image Processing

• Overview of Signals and Images

• Basic Signal Properties

• Image Representation

• Sampling and Quantization

2. Fourier Analysis

• Continuous Fourier Transform

• Discrete Fourier Transform (DFT)

• Properties of the DFT

• Fast Fourier Transform (FFT)

• Applications of Fourier Analysis in Signal Processing

3. Wavelet Theory

• Introduction to Wavelets

• Continuous Wavelet Transform

• Discrete Wavelet Transform

• Multiresolution Analysis

• Construction of Wavelets

• Properties of Wavelets

4. Applications to Signal Processing

• Signal Denoising

• Compression Techniques

• Feature Extraction

• Time-Frequency Analysis

• Filter Banks and Wavelet Packets

5. Applications to Image Processing

• Image Denoising and Restoration

• Image Compression (JPEG2000)

• Edge Detection and Texture Analysis

• Image Segmentation

• Image Enhancement

6. Advanced Topics

• Frame Theory

• Lifting Schemes

• Biorthogonal Wavelets

• Multidimensional Wavelets

• Recent Advances and Research Directions

7. Software and Practical Implementations

• Matlab/Python Toolboxes for Wavelets and Fourier Analysis

• Algorithm Optimization

• Case Studies

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Tags: S Allen Broughton, Kurt Bryan, Discrete Fourier, Analysis