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

Time for action – implementing a spatiotemporal averaging filter


Now that we know the steps of the process, we can write a function that performs it. The function will have some similarities to the spatiotemporal deinterlacing function implemented in the previous example. It will take as input a grayscale video in a matrix variable (if it is not grayscale it will convert each frame to grayscale) and the filtering neighborhood, and will produce as output a matrix containing the filtered video:

function [vid] = SpatioTemporalAveraging(vid,nhood)
 
% Function for de-interlacing a video using Field Merging
% Inputs:
%        vid     – Input video matrix (we assume grayscale video) 
%        nhood   - Dimensions of filtering neighborhood
% Output:   
%        vidOut     - Output video matrix (filtered)
 
vid = single(vid);  % Convert matrix to single to perform averaging
  vidOut = zeros(size(vid)); % Create a zero-valued matrix to hold the result
  % For all frames except the ones that fall off...