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Image Processing for Engineers

by Andrew Yagle, Fawwaz Ulaby

Image Processing for Engineers

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Book Description

This is an image processing textbook with a difference. Instead of just a picture gallery of before-and-after images, we provide (on the accompanying website) MATLAB programs (.m files) and images (.mat files) for each of the examples. These allow the reader to experiment with various parameters, such as noise strength, and see their effect on the image processing procedure. We also provide general MATLAB programs, and Javascript versions of them, for many of the image processing procedures presented in this book. We believe studying image processing without actually performing it is like studying cooking without turning on an oven.

Designed for a course on image processing (IP) aimed at both graduate students as well as undergraduates in their senior year, in any field of engineering, this book starts with an overview in Chapter 1 of how imaging sensors - from cameras to radars to MRIs and CAT - form images, and then proceeds to cover a wide array of image processing topics. The IP topics include: image interpolation, magnification, thumbnails, and sharpening, edge detection, noise filtering, de-blurring of blurred images, supervised and unsupervised learning, and image segmentation, among many others. As a prelude to the chapters focused on image processing (Chapters 3 - 12), the book offers in Chapter 2 a review of 1-D signals and systems, borrowed from our 2018 book Signals and Systems: Theory and Applications, by Ulaby and Yagle.

This open book is licensed under a Open Publication License (OPL). You can download Image Processing for Engineers ebook for free in PDF format (58.9 MB).

Table of Contents

Chapter 1
Imaging Sensors
Chapter 2
Review of 1-D Signals and Systems
Chapter 3
2-D Images and Systems
Chapter 4
Image Interpolation
Chapter 5
Image Enhancement
Chapter 6
Deterministic Approach to Image Restoration
Chapter 7
Wavelets and Compressed Sensing
Chapter 8
Random Variables, Processes, and Fields
Chapter 9
Stochastic Denoising and Deconvolution
Chapter 10
Color Image Processing
Chapter 11
Image Recognition
Chapter 12
Supervised Learning and Classification

Book Details

Image Processing for Engineers
Computer Science
Michigan Publishing
ISBN13 Digital
ISBN10 Digital
PDF Size
58.9 MB
Open Publication License

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