MATLAB Programming
MATLAB is a programming language developed by MathWorks. It started out as a matrix programming language where linear algebra programming was simple. It can be run both under interactive sessions and as a batch job.
Most MATLAB scripts and functions can be run in the open source programme octave. This is freely available for most computing platforms.
GNU Octave and LabVIEW MathScript are systems for numerical computations with an mfile script language that is mostly compatible with MATLAB. Both alternatives can replace MATLAB in many circumstances. While a good deal of the content of this book will also apply to both Octave and LabVIEW MathScript, it is not guaranteed to work in exactly the same manner. Differences and comparison between MATLAB and Octave are presented in Comparing Octave and MATLAB.
Contents
 1 A Tutorial Introduction
 2 Basic MATLAB Concepts
 3 Data Storage and Manipulation
 4 Graphics
 5 Mfile Programming
 6 Numerical Manipulation
 7 More advanced I/O
 8 Examples
 9 Object Oriented Programming
 10 An alternative to MATLAB: Octave
 11 Toolboxes and Extensions
 12 MATLAB in medicine
 13 References
 14 External links
 15 Other Wikibooks
 16 Organization
A Tutorial Introduction[edit]
Basic MATLAB Concepts[edit]
Saving and loading a MATfile[edit]

 Commands
 File Naming conventions
 Basic Reading and Writing data from a file
clc; clear all; close all;
[filename, pathname] = uigetfile( {'*.jpg';'*.bmp'}); aa=imread([pathname,filename]); I=aa; bb=imresize(aa,[256 256]); imshow(bb);title('input image');
%%...............%%% RGB2Lab color conversion %%%.........
rgbimage=makecform('srgb2lab'); labimage=applycform(bb,rgbimage); figure, imshow(labimage);title('color conversion image');
%%..............%%% seperate L* a* b* color space %%%.........
L=im2double(labimage(:,:,1)); a=im2double(labimage(:,:,2)); b=im2double(labimage(:,:,3)); figure,imshow(L);title('L* image'); [h,w,o]=size(L);
%%..........%%% applying filter in L* color space %%%..........
for s=1:3
W(s)=h/2^s; for i=1:h for j=1:w p=(iW(s)); q=(i+W(s)); r=(jW(s)); t=(j+W(s)); if p<=0 p=1; end if q>256 q=256; end if r<=0 r=1; end if t>256 t=256; end m=p:q; n=r:t; %N(s)=W(s)*W(s); N(s)=size(m,2)*size(n,2); sum1=sum(sum(L(m,n))); V=1/N(s); A=V*sum1; B(i,j)=L(i,j)A; end end %B=LA; %figure,imshow(B); azx(:,:,s)=B;
end
contrast_L=azx(:,:,1)+azx(:,:,2)+azx(:,:,3); figure,imshow(contrast_L),title('contrast map L* image');
%%..............%%% find inverse of a* %%%............
figure,imshow(a);title('a* image'); d=max(max(a)); yy=da; yy=(yy*5); figure,imshow(yy);title('inv a* image'); [h,w,o]=size(yy);
%%.............%%% applying filter in a* color space %%%........
for s=1:3
W(s)=h/2^s; for i=1:h for j=1:w p=(iW(s)); q=(i+W(s)); r=(jW(s)); t=(j+W(s)); if p<=0 p=1; end if q>256 q=256; end if r<=0 r=1; end if t>256 t=256; end m=p:q; n=r:t; %N(s)=W(s)*W(s); N(s)=size(m,2)*size(n,2); sum1=sum(sum(yy(m,n))); V=1/N(s); A=V*sum1; C(i,j)=yy(i,j)A; end end %C=LA; %figure,imshow(C); aza(:,:,s)=C;
end
contrast_a=aza(:,:,1)+aza(:,:,2)+aza(:,:,3); figure,imshow(contrast_a),title('contrast map a* image');
%%.............%%% find final scaling contrast map %%%.......
Scaling_contrast=imadd(contrast_L,contrast_a); figure,imshow(Scaling_contrast),title('Scaling contrast map');
%%...........%%% gabor filter outputs %%%.......................
[gabor_timage,u,v,GT,filter]=final_gabor(aa);
%%..........%%% removing erythema & dark pixels %%%..........
ts=0.4; %% set threshold value R=Scaling_contrast; for i=1:h
for j=1:w if Scaling_contrast(i,j)>=ts R(i,j)=1; else R(i,j)=0; end end
end
figure,imshow(R);title('Removing erythema');
The MATLAB Command Prompt[edit]

 Calculator
Data Storage and Manipulation[edit]
Data Types and Operators on Point Values[edit]
Arrays and Matrices[edit]
Graphics[edit]
Graphics[edit]
Handle Graphics[edit]
 What is a handle?
 Figure handles
 Axis handles
 Other types of handles
Annotating Plots[edit]
Mfile Programming[edit]
Scripts[edit]
Control Flow[edit]
Error Messages[edit]
Debugging M Files[edit]
Numerical Manipulation[edit]
Linear Algebra[edit]
It is the Matrix laboratory after all.

 Operations
 Transpose
 Systems of linear equations

 Row reduced echelon form
 Inverse
 Coffactor, minor
 Jacobian
Differential Equations[edit]
More advanced I/O[edit]
Different versions of MATLAB handle this differently. We will focus on versions 6.5 and 7.x, primarily on MATLAB 7.x since it is the latest. A note will appear when the procedure is different for ver. 6.
Reading and writing from files[edit]
Writing and Reading to A Serial Port[edit]
Writing to a USB port[edit]
Examples[edit]
Filtering[edit]

 Moving Average
 Alpha Beta
 Kalman

 PSD estimation
 Entropy
 Markov Processes
 Queuing Theory
Controls[edit]
Phase vocoder[edit]
See "Phase vocoder and encoder in MATLAB" for an example phase vocoder and the corresponding sound sample encoder in MATLAB.
Object Oriented Programming[edit]
MATLAB as well as Octave have object oriented capabilities. Yet, technically it is not fully an object oriented language.
An Object Oriented Language(OOL) has three components: 1. Polymorphism 2. Inheritance 3. Encapsulation
Octave can be extended by adding new objects. Those objects can overload the operators like e.g. assignment, slicing, comparison.
While in MATLAB, this can be done with mscript, in Octave new objects are implemented as C++ classes. A simple example of how objects can be added to Octave can be found here.
Struct arrays[edit]
MATLAB classes[edit]
An alternative to MATLAB: Octave[edit]
What is Octave ?[edit]
A short presentation of Octave and its history.
Differences between Octave and MATLAB[edit]
The most important differences between Octave and MATLAB that anyone willing to use Octave instead of MATLAB should be aware of.
Toolboxes and Extensions[edit]
The toolboxes are pretty good if you can afford them. In version 7 there are a lot of toolboxes.
Symbolic Toolbox[edit]
Image Processing Toolbox[edit]
MATLAB Compiler[edit]
Legacy Toolboxes[edit]
 GUIDE allows the creation of interactive user interfaces.
 Simulink is for modeling, simulating and analysing systems.
 Psychtoolbox is a set of tools that aid in vision research.
 Distributed computing The distributed computing toolbox is a set of tools that aid in distributing models over a cluster.
 Optimization The optimization toolbox includes various algorithms for minimization.
MATLAB in medicine[edit]
„Image Processing in Optical Coherence Tomography using Matlab” is a book which will introduce you to subtleties related to the implementation of selected fragments of algorithms, the notation of some of them in the MATLAB environment has been given. The presented source code is shown only in the form of example of implementable selected algorithm. The book is addressed to ophthalmologists , IT specialists and students involved in the development of applications designed for automation of measurements for the needs of medicine.
References[edit]
 MATLAB documentation from The MathWorks.
 MATLAB programs compilation from 'MATLAB programs for Engineering Students'.
External links[edit]
 MATLAB at literateprograms.org
 ControlTheoryPro.com MATLAB Category
 Processing in Optical Coherence Tomography using Matlab
 programs compilation for Engineering Students
Other Wikibooks[edit]
A number of other wikibooks use MATLAB to teach their subjects. The following wikibooks make use of MATLAB: