Gulsah Tumuklu Ozyer

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MATLABIMAGE PROCESSING TOOLBOX

• Gulsah Tumuklu Ozyer

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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

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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

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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
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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

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Logical Conditions

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

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Logical Conditions(cont.)

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

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Flow Control

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

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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.

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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

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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

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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

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Read and Write Images

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

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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

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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

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• 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

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• 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.

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• 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.

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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.

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• 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)

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• 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)

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Morphological Operations

• Dilation imdilate()
• Erosion imerode()
• Closing imclose()
• Opening imopen()

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Color

• The available colorspaces
• RGB, NTSC (US televisions), YCbCr (Digital
  video), HSV.
• Transformations between the spaces
• rgb2ntsc, hsv2rgb,

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• Questions?