Computer ScienceScience & MathematicsEconomics & FinanceBusiness & ManagementPolitics & GovernmentHistoryPhilosophy

Image Processing for Engineers

by Andrew Yagle, Fawwaz Ulaby

Image Processing for Engineers

Subscribe to new books via dBooks.org telegram channel

Join
DescriptionTable of ContentsDetailsHashtagsReport an issue

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

Title
Image Processing for Engineers
Subject
Computer Science
Publisher
Michigan Publishing
Published
2018
Pages
438
Edition
1
Language
English
ISBN13
9781607854883
ISBN10
1607854880
ISBN13 Digital
9781607854890
ISBN10 Digital
1607854899
PDF Size
58.9 MB
License
Open Publication License

Related Books

Cloud-Based Benchmarking of Medical Image Analysis
This book presents the VISCERAL project benchmarks for analysis and retrieval of 3D medical images (CT and MRI) on a large scale, which used an innovative cloud-based evaluation approach where the image data were stored centrally on a cloud infrastructure and participants placed their programs in virtual machines on the cloud. The book presents the...
Medical Imaging Systems
This book gives a complete and comprehensive introduction to the fields of medical imaging systems, as designed for a broad range of applications. The authors of the book first explain the foundations of system theory and image processing, before highlighting several modalities in a dedicated chapter. The initial focus is on modalities that are clo...
Computer and Information Sciences
This book constitutes the refereed proceedings of the 31st International Symposium on Computer and Information Sciences, ISCIS 2016, held in Krakow, Poland, in October 2016. The 29 revised full papers presented were carefully reviewed and selected from 65 submissions. The papers are organized in topical sections on smart algorithms; data classific...
Deep Learning with JavaScript
Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the main authors of t...
Data and Text Processing for Health and Life Sciences
This book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and...
Computer Vision Metrics
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, ...