Computer Assisted Image Analysis TF 3p and MN1 5p Lecture 1, (GW 1, )

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1 Centre for Image Analysis Computer Assisted Image Analysis TF p and MN 5p Lecture, 422 (GW, ) 2.4) 2 Why put the image into a computer? A digital image of a rat. A magnification of the rat s nose. Intensity values of the rat s nose " % # 4 & Digital Images: Applications ' Multi spectral satellite image Microscopy image of wood 5 Areal image of a forest Multi spectral areal image of the Stockholm archipelago 6

2 ( Medical applications Medical Applications ) ( X-ray image MR (Magnetic Resonance) PET (Positron Emission Tomography) stained cell nuclei in cancer tumor cultured and stained cells (Fluorescens microscopy) living neural stem cells (Light microscopy) 7 8 Course contents +%, -. / Problem Image acqusition The Fundamental Steps in Digital Image Processing Preprocessing Segmentation Solution Recognition and interpretation Representation and description data Image Analysis (bildanalys) vs Image Processing ( bildbehandling) world Visualisation Image Analysis (Bildanalys) Computer Graphics (Datorgrafik) knowledge Imaging image Image Processing (Bildbehandling) Image understanding (Bildförståelse) Computer vision (Datorseende) Course goals 4 how a digital image works. when image analysis could be a possible solution. when image analysis is not a possible solution. what the requirements on the equipment are. what the requirements on the image are. how to do some image processing and analysis yourself. what is true and false about imaging and analysis systems. that some images tell lies.. 2 2

3 Digital images Image sampling (x,y) A 2D gray-scale image f(x,y) the value of f(x,y) is the grey-level or intensity at position (x,y) A digital image must be sampled (digitized): in space (x,y): image sampling (S: rastrering) in amplitude f(x,y): grey-level quantization (S: kvantisering) 4 Image sampling (x,y( x,y) Methods for image sampling (in space) Uniform - same sampling frequency everywhere Adaptive - higher sampling frequency in areas with greater detail (not very common) The discrete sample is called a pixel (from picture element) in 2D and voxel (from volume element) in D and is usually square (cubic), but can also have other shapes (i.e. hexagonal grids) :6 Computer Assisted Image Analysis 5 6 ). ; < " 65 ; <. Grey-level quantization 657 :

4 Grey-level quantization Methods for quantization (in amplitude) Uniform (linear) the intensities of the object are mapped directly to the gray-levels of the image Logarithmic - higher intensity resolution in darker areas (the human eye is logarithmic) image intensity image intensity object intensity object intensity Common quantization levels Choice of sampling f(x,y) is given integer values [-max], max=2 n - n= [ ] binary image n=5 [ ] maximum the human eye can resolve (locally) n=8 [ 255] byte, very common n=6 [ 6555] common in research n=24 [ ] common in color images (i.e. 8 for RGB) What will the image be used for? What are the limitations in memory and speed? Will we only use the image for visual interpretation or do we want to do any image analysis? What information is relevant for the analysis (i.e. color, spatial and/or gray-level resolution)? 2 22 Re-sampling Resampling by interpolation Strategy : take the nearest neighbor (NN) T Re-sampling: g(x,y) f(x,y) Strategy 2: use bi-linear interpolation Make two (three) interpolations between 4 neighbors f(x,y ) f(x,y ) f(x 2,y ) f(x,y) x x f ( x, y) = f ( x, y) + ( f ( x2, y) f ( x, y)) x2 x result of NN: f(x,y 2 ) f(x,y 2 ) f(x 2,y 2 ) x x f ( x, y2 ) = f ( x, y2 ) + ( f ( x2, y2 ) f ( x, y2 )) x x 2 y y f ( x, y) = f ( x, y) + ( f ( x, y2 ) f ( x, y)) y y

5 original image rotation with NN interpolation rotation with bi-linear interpolation The image information may be obscured if the sampling frequency is different from frequencies in the image '" AA #6 #: #9 The frequency of thin lines is too low to be correctly represented when the image is sub-sampled to ¼ of its size. This image was scanned from a magazine, resulting in a pattern due to the frequency of the raster in the printing. AA #6 #: # images from 5