Change detection using Mean ratio operator

    change detection is nothing but process of detecting difference between two different images . this can also be performed  by using Mean Ratio operator  give below 

µ1, µ2 is local mean values of images A and B.

the underlying idea of the optimal difference image is that unchanged pixels exhibit small values,whereas changed areas exhibit larger values. it show  changed region  but it doesn't enhance it.result is better then that of log ratio operator

procedure is giveb below

STEP1 : clear previous project variable, clear history , and close all the window

STEP2 : Read the two source images as A and B

Change detection using log ratio operator

    change detection is nothing but process of detecting difference between two different images . this can be performed  by using Log Ratio operator


The logarithmic operator is characterized by enhancing the low-intensity pixels while weakening the pixels in the areas of high intensity;therefore,the information of changed regions that is obtained by the log-ratio image may not be able to reflect the real changed trends in the maximum extent because of the weakening in the
areas of high-intensity pixels.

procedure is giveb below

STEP1 : clear previous project variable, clear history , and close all the window
STEP2 : Read the two source images as A and B

Neighbourhood operation in image processing

        Generally neighborhood operations is performed by the following command

Syntax

B = nlfilter(A, [m n], fun)
B = nlfilter(A, 'indexed',...)

Description

B = nlfilter(A, [m n], fun) applies the function fun to each m-by-n sliding block of the grayscale image A. fun is a function that accepts an m-by-n matrix as input and returns a scalar result.

IMAGE REGISTRATION

 

What is Image Registration ?

           In many situations one has two or more images of the same object where the differences between the images have to do with acquisition times, dissimilar acquisition hardware or changes in the shape of the object between exposures. To facilitate comparison between such images it is necessary to register them, i.e., to adjust them so that they match each other.

ARITHMETIC OPERATIONS ON IMAGE

 

Arithmetic operations addition,subtraction, division,and multiplication which is performed pixel by pixel between two images or among many images

Addition operation

which is also called pixel addition. addition operator add two images in pixel by pixel fashion .matlab coding is given below
coding :

READING,DISPLAYING AND WRITING AN IMAGE

Reading Image

the images are read into matlab environment ( for processing) using the command line given below
>> ima=imread(‘filename’);
here filename is the name of the image file including file extension and ima is variable that store the image in the format of matrix

SPATIAL TRANSFORMATION part-2

Rotate image

Syntax
B=imrotate(A,angle)
B=imrotate(A,angle,method)
B = imrotate(A,angle,method,bbox)

Description

SPATIAL TRANSFORMATION part-1

SPATIAL TRANSFORMATION

     A spatial transformation (also known as a geometric operation) modifies the spatial relationship between pixels in an image, mapping pixel locations in an input image to new locations in an output image. For simplicity, assume that the image I being considered is formed by projection from scene S (which might be a two- or three-dimensional scene, etc.).
   The spatial domain is the normal image space, in which a change in position in I directly projects to a change in position in S. Distances in I (in pixels) correspond to real distances (e.g. in meters) in S.
Resize image

IMAGE CONVERSION

Convert image to binary image, based on threshold

X=imread(‘trees.tif’);
BW = im2bw(X, map,0.4);
subplot(1,2,1), subimage (X), subplot(1,2,2), subimage (BW);

IMAGE TYPES AND CONVERSIONS

 
IMAGE TYPES
The Image Processing Toolbox supports four basic types of images:

• Binary images
• grayscale images
• Indexed images
• RGB images

This section discusses how MATLAB and the Image Processing Toolbox represent each of these image types.

INTRODUCTION TO MATLAB part-4

Help

Help for functions in Command Window
Syntax
help
help ops
help functionname
help modelname.mdl
help methodname
help classname
help packagename
help classname.name

INTRODUCTION TO MATLAB part-3

MATLAB FUNCTIONS

EDITING FILES

Exit

Terminate MATLAB program (same as quit)
Syntax
exit
Description
exit terminates the current session of MATLAB after running finish.m, if the file finish.m exists. It performs the same as quit and takes the same termination options, such as force

INTRODUCTION TO MATLAB part-2

Inbuit Command in Matalb

STARTUP AND SHUTDOW

exit	Terminate MATLAB program (same as quit)
finish	Termination file for MATLAB program
matlab (UNIX)	Start MATLAB program (UNIX platforms)
matlab (Windows)	Start MATLAB program (Windows platforms)
matlabrc	Startup file for MATLAB program
prefdir	Folder containing preferences, history, and layout files
preferences	Open Preferences dialog box
quit	Terminate MATLAB program
startup	Startup file for user-defined options
userpath	View or change user portion of search path

INTRODUCTION TO MATLAB part-1

MATLAB BASICS
What Is MATLAB?
MATLAB is a high-performance language for technical computing. It integrates computation, visualization, and programming in an easy-to-use environment where problems and solutions are expressed in familiar mathematical notation.