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MATLAB IMAGE PROCESSING TOOLBOX Gulsah Tumuklu Ozyer Introduction MatLab : Matrix Laboratory A high-level language for matrix calculations, numerical analysis ... – PowerPoint PPT presentation

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Title: Gulsah Tumuklu Ozyer

1
MATLABIMAGE PROCESSING TOOLBOX

Gulsah Tumuklu Ozyer

2
Introduction

MatLab Matrix Laboratory
A high-level language for matrix calculations,
numerical analysis, scientific computing
Programming
Can type on command line, or use a program file
(m-file)
Semicolon at end of line is optional (suppresses
printing)
Control flow (if, for, while, switch,etc) similar
to C
Differences from C no variable declarations, no
pointers

3
MATLABs Workspace

who,whos - current variables in workspace
save - save workspace variables to .mat file
load - load variables from .mat file
clear all - clear workspace variables

4
Matlab Basics

Everything is a matrix
a variable is a 1x1 matrix
Initializing a matrix
Example my_matrix 1 2 3 4 5 6 7 8 9
Accessing a matrix (row, column)
my_matrix(1,2) has the value 2
Colon operator generates a range
Example 110 1 2 3 4 5 6 7 8 9 10
mytest(1, 24) is equivalent to mytest(1,2 3 4)
mytest(3, ) refers to all elements of row 3

my_matrix 1 2 3 4 5 6 7 8 9
5
Basic Operations on Matrices

All the operators in MATLAB defined on matrices
, -, , /, , sqrt, sin, cos etc.
Element wise operators defined with
preceding dot ., ./, . .
size(A) - size vector
sum(A) - columns sums vector
sum(sum(A)) - all the elements sum

6
Logical Conditions

, lt , gt , (not equal) ,(not)
find(condition) - Returns indexes of As
elements that satisfies the condition.

7
Logical Conditions(cont.)

Example
gtgt A 1 2 3 4, I find(Alt4)
A
1 2
3 4
I
1
2
3

8
Flow Control

MATLAB has five flow control constructs
if statements
switch statements
for loops
while loops
break statements

9
Scripts and Functions

There are two kinds of M-files
Scripts, which do not accept input arguments or
return output arguments. They operate on data in
the workspace.
Functions, which can accept input arguments and
return output arguments. Internal variables are
local to the function.

10
Visualization and Graphics

plot(x,y), plot(x,sin(x)) - plot 1-D function
figure , figure(k) - open a new figure
hold on, hold off - refreshing
mesh(x_ax,y_ax,z_mat) - view surface
contour(z_mat) - view z as top. map
subplot(3,1,2) - locate several plots in figure
axis(xmin xmax ymin ymax) - change axes
title(figure title) - add title to figure

11
The Image Processing Toolbox

The Image Processing Toolbox is a collection of
functions that extend the capability of the
MATLAB numeric computing environment. The
toolbox supports a wide range of image processing
operations, including
Geometric operations
Neighborhood and block operations
Linear filtering and filter design
Transforms
Image analysis and enhancement
Binary image operations

12
MATLAB Image Types

Indexed images m-by-3 color map
Intensity images 0,1 or uint8
Binary images 0,1
RGB images m-by-n-by-3

13
Read and Write Images

I imread(colors.jpg')
imshow(I)
Indexed Image
x,map imread(color.png')
imwrite(I, newim.jpg)

14
Image Display

image - create and display image object
imagesc - scale and display as image
imshow - display image
colorbar - display colorbar
getimage- get image data from axes
truesize - adjust display size of image
zoom - zoom in and zoom out of 2D plot

15
Image Conversion

gray2ind - intensity image to index image
im2bw - image to binary
im2double - image to double precision
im2uint8 - image to 8-bit unsigned integers
im2uint16 - image to 16-bit unsigned integers
ind2gray - indexed image to intensity image
mat2gray - matrix to intensity image
rgb2gray - RGB image to grayscale
rgb2ind - RGB image to indexed image

Geometric Operations
Image resizing imresize(I,x y,method).
Method is bilinear, bicubic or nearest
neighbours.
Image rotation imrotate(I,angle,method) method
is same as before. Zero padding in the rotated
image.
Image cropping Jimcrop

Neighbourhood Processing
To speed up neighbourhood processing transform
every neighbourhood to column vector and perform
vector operations.
The borders are usually padded with zeros for the
computations of the edges neighborhoods.
Linear filtering can be done with convolution
- conv2(Img, h) or correlation
- filter2(Img, h).
Nonlinear filtering nlfilter(I,sx sy,func)
where func is a function that recieves the
windows and returns scalars.

Transforms
Fourier and inverse Fourier transform
Ffftshift(fft2(f)) F is a complex matrix
Frealreal(F)Fimagimag(F)Fabsabs(F)Fphsangle
(F)
imshow(Freal)
fifft2(F)
DCT and compression
Iimread(cameraman.tif)
Iim2double(I)
Tdctmtx(8)
Bblkproc(I,8 8, P1xP2,T,T)
mask1 1 1 0 0
B2blkproc(B,8 8,P1x,mask)
I2blkproc(B2,8 8,P1xP2,T,T)
It is also possible to use dct2 and idct2.

19
Analyzing and Enhancing Images

pixval returns the value of a pointed pixel and
the distance between two pointed pixels.
impixel returns the data value for a selected set
of pixels. The set can be pointed by the mouse or
by coordinates.
imcontour plots the contours of the image.
imhist(I,n) plots the histogram of I with n bins.

Edge detection
edge(I,sobel)
edge(I,canny)
Or by fspecial(sobel) and conv2.
Image Enhancement
Histogram stretching
imadjust(I,low high,bottom top)
Gamma correction
imadjust(I,,,gamma_coef)
Histogram Equalization
histeq(I)

Noise removal
To add noise to an image
imnoise(I,type,coef) type can be salt n
pepper, speckle, gaussian for SP,
multiplicative and additive noise.
Averaging or gaussian filtering
Ffilter2(fspecial(average,3),J)
Median filtering
Fmedfilt(J,3 3)

22
Morphological Operations