Programming for image analysis

Programs for:image ANALYSISimage processing

tools for writing your own programs

fundamental steps

knowledge base

CHAPTER 2imageacquisition

CHAPTER 3&4imageenhancement

CHAPTER 5imagerestoration

CHAPTER 6color imageprocessing

CHAPTER 7wavelets andmultiresolutionprocessing

CHAPTER 8compression

CHAPTER 9morphologicalprocessing

CHAPTER 10segmentation

CHAPTER 11representation& description

CHAPTER 12objectrecognition

problem

xv

• xv is an interactive image manipulation program for the X Window System

• grab

available at IT

http://www.trilon.com/xv/

grab image

ALGORITHMS• filters

• blur, sharpen, ...• geometric transforms

• rotate, ...

WINDOWS à color editor• histogram equalization, contrast stretch, ...

xv color editor

gimp

• GNU Image Manipulation Program – paint program, photo retouching, image

composition, ...

• free

”If you enjoy using Adobe's Photoshop® program, you'll love the GIMP” .....

http://www.gimp.org/

gimp example

layers

”enhancement”

ENVI

• ENvironment for Visualizing Images

• developed for remote sensing and GIS

http://www.rsinc.com/envi

image enhancement

IDL

• Interactive Data Language• for data analysis and visualization• used to write ENVI

http://www.rsinc.com/idl/

VIP

• Visual IDL Programming environment• programming IDL without knowing the

language

http://www.rsinc.com/vip/

khoros

• tool boxes for– visualization: multispectral, 3D– image processing– data manipulation

• visual programming

http://www.khoral.com/khoros/

VTK

• Visualization ToolKit• C++ class library, and

several interpreted interface layers (Tcl/Tk, Java, Python...)

• free

http://public.kitware.com/VTK/

MATLAB

• MATrix LABoratory– most suited for matrix operations

• not: for x=1:n for y=1:n, ...

• image processing toolbox– help images– helpdesk

http://www.mathworks.com/products/image/

available at IT

image processing toolbox

• from MATLAB and Signal Processing Toolbox

• read/write a number of image formats• predefined functions

– image transforms– filtering– enhancement– feature extraction

imagesbasic structure in MATLAB is the arrayà image is (often) stored as 2D array

each element in matrix (image I) = pixeladdressed I(x,y)

many predefined functions for image processing and analysis ((often) well described)

write your own programs!!!!

image representation

• indexed images– image array I, colormap C

(index à colour)

• intensity images– 2D array– element = pixel– intensity value [0,1]

• binary images– special kind of intensity

image– pixels have value 0 (white)

or 1 (black)

• RGB images– 3D array (MxNx3)– MxN intensity image for red,

green, blue component• uint8-type à 8-bit images

– each pixel is 1 byte with values from 0 to 255

• uint16-type à 16-bit images– each pixel is 2 byte with

values from 0 to 65535

double or uint8/uint16

I/O: read and write

• imread– I=imread(’imagename.tif’,’tif’)

• imwrite– imwrite(I,’imagename.tif’,’tif’)

X Windows Dump (XWD)'xwd'

Tagged File Format (TIFF)'tif' or 'tiff'

Portable Networks Graphics (PNG)’png'

Windows Paintbrush (PCX)'pcx'

Joint Photographic Experts Group (JPEG)

'jpg' or 'jpeg'

Windows Icon resources (ICO)'ico

Hierarchical Data Format (HDF)'hdf'

Graphics Interchange Format (GIF)'gif'

Windows Cursor resources (CUR)'cur'

Windows Bitmap (BMP)’bmp’

File TypeFormat

conversions

mat2graymatrix à intensity

rgb2grayRGBà intensity

im2bwindexed, intensity, RGB à BWTHRESHOLDING

im2uint8, im2uint16indexed, intensity, RGB à uint8

im2doubleuint8 à indexed, intensity, RGB

image arithmetics

• MATLAB arithmetic operators (+, -, ...) do not accept uint8 or uint16 data– ... out of range ...– new version: imadd,

imsubtract, ...• enhancement

– change brightness/add constant: brighten

– change contrast&brightness: imadjust

• image arithmetics– convert to double

• logical operations– binary image

• &, ~,...

coordinate system

I(row,column)x

y

upper left corner = (1,1)

pixel coordinatesdiscrete

spatial coordinates continuous

upper left corner = (0.5,0.5)

displaying imagesimshow(nameOfImage)

display by using image (& imagesc) functionà Handle Graphics imageobject

imshow automatically sets Handle Graphics properties and attributes to optimize display

spatial transformations

• interpolation– nearest neighbour (1)– bilinear (2x2)– bicubic (4x4)

• resizing– imresize

• rotation– imrotate

• cropping

imresizeimshow(bil)

bilX=imcrop(bil,[X Y cutSize cutSize]);imshow(bilX)

Small=0.6;bilSmall=imresize(bil, Small,'bilinear');bilSmallX=imcrop(imshow(bilSmallX)

Large=2.5;bilLarge=imresize(bil, Large,'bilinear');bilLargeX=imcrop(imshow(bilLargeX)

imrotate

imshow(bil)

rot=25;bilRotN=imrotate(bil,rot,'nearest');bilRotBL=imrotate(bil,rot,'bilinear');

imshow(bilRotN)

bilNX=imcrop(bilBLX=imcrop(

imshow(bilNX)

imshow(bilBLX)

histogram processing

• histogram of an image– imhist

• contrast stretching– imadjust

• histogram equalization– histeq

bil2=imadjust(bil,[10/255 210/255],[]);imshow(bil2)imhist(bil2)

bilEq=histeq(bil);imshow(bilEq)imhist(bilEq)

filtering

• predefined (fspecial)• design own filters

– MxN matrix with entries ∈[0,1]– centre in (M/2,N/2)

• apply filter using filter2• predefined edge filters: edge

bilEdge=edge(bil,'sobel');

fGaussian=fspecial('gaussian')bilGaussian=im2uint8(filter2(fGaussian,im2double(bil)));

filtSize=5;fMean=ones(filtSize,filtSize)/(filtSize*filtSize)bilMean=im2uint8(filter2(fMean,im2double(bil)));

fSobel = 1 2 10 0 0-1 -2 -1

fGaussian = 0.0113 0.0838 0.01130.0838 0.6193 0.08380.0113 0.0838 0.0113

image transforms

• image usually function of two (three) spatial variables f(x,y)

• transformation gives an alternative representation – Fourier transform– discrete cosine transform

Fourier transform

fft, fft2, and fftn implement fast Fourier transform algorithm for computing the one-dimensional DFT, two-dimensional DFT, and N-dimensional DFT, respectively.Functions ifft, ifft2, and ifftn compute the inverse DFT.

possible to create and applyfilters in frequency domain: highpass, lowpass, bandpass, ...

use FFT

freqdist=imread('images/freqdist.tif');

imshow(freqdist)

freqdistFFT=fft2(freqdist);

imshow(log(abs(fftshift(freqdistFFT))),[])

same as centreshift in IMP

binary image operations

• thresholding• labelling• simple descriptors

– area, perimeter, euler number

• morphological operators

create binary image

imshow(circles)

imhist(circles)

thresCircles=im2bw(circles,150/255);imshow(thresCircles)

invCircles=~thresCircles;imshow(invCircles)

label imageselect connected component

imshow(invCircles)

[circlesID nrCirc]=bwlabel(invCircles,8);

imshow(circlesID,[])

oneID=bwselect(circlesID,8);

imshow(oneID,[])

morphology

structuring element defined by • MxN matrix of 0s and 1s• origin in (M/2,N/2)

imshow(tower)

SE=[1 1 1; 1 1 1; 1 1 1];

towerShrink=erode(tower,SE);imshow(towerShrink)

towerGrow=dilate(tower,SE);imshow(towerGrow)

added

• distance transform with applications– watershed, ...

• more morphology• more image formats• image arithmetics

– imadd, imsubtract, imlincomb, ...

other tool boxes for MATLAB

• the 'Q' Software– http://www.cs.dartmouth.edu/~farid/tutorials/tutorials.html

• DIP image– http://www.ph.tn.tudelft.nl/DIPlib/

• [SDC Morphology Toolbox– http://www.mmorph.com/]

ImageJ

• image processing and analysis in Java• easy to add own (or others’) plugins• can be run as applet• free

http://rsb.info.nih.gov/ij/

thresholding

measurements

write own IJ plugins

• Java complier needed• added under Plugins• recorder function exists

ImagePlus – image object:COLOR_256COLOR_RGBGRAY32GRAY16GRAY8

• getPixel, setPixel, ...• ROI - region of interest to work on part of image• draw• use already exisiting functions• and more....