Book Image

Visual Media Processing Using MATLAB Beginner's Guide

By : George Siogkas
Book Image

Visual Media Processing Using MATLAB Beginner's Guide

By: George Siogkas

Overview of this book

Whether you want to enhance your holiday photographs or make a professional banner image for your website, you need a software tool that offers you quick and easy ways to accomplish it. All-in-one tools tend to be rare, and Matlab is one of the best available.This book is a practical guide full of step-by-step examples and exercises that will enable you to use Matlab as a powerful, complete, and versatile alternative to traditional image and video processing software.You will start off by learning the very basics of grayscale image manipulation in Matlab to master how to analyze 3-dimensional images and videos using the same tool. The methods you learn here are explained and expanded upon so that you gradually reach a more advanced level in Matlab image and video processing. You will be guided through the steps of opening, transforming, and saving images, later to be mixed with advanced masking techniques both in grayscale and in color. More advanced examples of artistic image processing are also provided, like creating panoramic photographs or HDR images. The second part of the book covers video processing techniques and guides you through the processes of creating time-lapse videos from still images, and acquiring, filtering, and saving videos in Matlab. You will learn how to use many useful functions and tools that transform Matlab from a scientific software to a powerful and complete solution for your everyday image and video processing needs.
Table of Contents (18 chapters)
Visual Media Processing Using MATLAB Beginner's Guide
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

The importance of binary images


To understand the notion of morphological operations, we will have to revisit the thresholding techniques presented in the previous chapter. We have already mentioned that thresholding an image leads to binary images, which are defined by their two possible pixel values; 0 (for black) and 1 (for white). The way to convert a grayscale image to binary is through thresholding; that is, setting the pixels above a certain value to 1 and the rest to 0. Let's now explain the basic reasons for binarizing an image. The purpose of image binarization can be split into two levels. At a first level, it is used to pinpoint the pixels of an image that interest us (usually called regions of interest or simply, ROIs), thus giving us a quick and easy overview of the image content. The binary images derived, are often called masks. At a second level, it can be used for processing only the selected ROIs (with pixel values equal to 1) defined by the mask, leaving the rest of the...