dr hab. Michał Strzelecki tel , room 216 cons. hours: Wednesday 14-15, Thursday P. Strumillo, M.

Transcription

1 dr hab. Michał Strzelecki tel , room 216 cons. hours: Wednesday 14-15, Thursday P. Strumillo, M. Strzelecki

2 One picture is worth more than ten thousand words Anonymous

3 Literature: 1. Lecture notes (*.pdf files) 2. R.C. Gonzales, R. E. Woods, Digital image processing, Addison-Wesley Publishing Company, J. C. Russ, The image processing handbook, IEEE Press, W. K. Pratt, Digital image processing, John Wiley &Sons, A. Materka, Elements of image processing (in Polish), PWN, 1991.

4 Assesment method: Theory: - written examination (50%). Practice: - project report and presentation (50%)

5 1. Improvement of subjective image quality (e.g. in 1964, computerised image processing techniques were applied for correcting distortions of images transmitted from moon space probe Ranger 7 Jet Propulsion Laboratory, USA) JPL JPL

6 Improvement of image quality MIT

7 ! " IOC, Antwerp 8 bpp JPEG 0.1 bpp Wavelet 0.1 bpp Playboy Magazine

8 Improvement of subjective image quality for human interpretation # $

9 Processing of image data for machine perception, storage or transmission FBI fingerprint database 1992 Biometry

10 Objectives of image Stereovision scene analysis Left camera image Right camera image Pseudocolored depth image Nearest objects extracted Reconstruction of depth

11 Electromagnetic spectrum frequency, Hz gamma rays X rays % radio waves ultraviolet Visible light Infrared waves [nm]

12 Image (90% of data) Decision

13 Image preprocessing Segmentation Feature extraction Image aquisition Computer + program + knowledge Image analysis and perception 9

14 1. Image acquisition and representation 2. Image enhancement 3. Image restoration 4. Image analysis 5. Image coding

15 Gray-scale transformation

16 Addison_Wesley Inc. motion blur restored image

17 !! # " & "! $ " %

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19 ) science and industry (quality control, sorting,...) medicine (X-ray images, computed tomography, MRI, USG, microscopy,...) army (target tracking, quided missiles, unmanned flying vehicles) robotics (welding, painting, robots,...) Earth and space exploration (interpretation of satellite images, space probes,...) Biometrics, human computer interaction systems.

20 radiography (J. Hall-Edwards, 1896) angiography (E. Honiz, 1927) ultrasonography CT tomography (A. Cormack, G. Hounsfield, 1972) since 80-ties) (I. Edler, C. Hertz, 1953) MRI tomography (P. Lauterbur, P. Mansfield, 1973 PET tomography (M. Ter-Pogossian i wsp., 1973) Endoscopic capsule (Given Imaging, 2001) endoscopy (B. Hirschowitz, since 70-ties

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31 Thermogram Visible light image Medicine Power eng. Civil eng.

32 H. Nowak Computer lip-reading, PhD project conducted at the Medical Electronics Division

33 J. Daugman

34 a concept of an image or a copy of an image database hit DWT C.E. Jacobs, A. Finkelstein, D.H. Salesis, Fast multiresolution image quering, 1999

35 * ", Ω f(x,y) y x y M : 2 Ω R R+ ( x, y) f ( x, y)

36 Distance along profile

37 RGB colour images R B G

38 RGB colour images Distance along profile RGB image and colour components profiles

39 , discretisation + quantization pixel (picture element)

40 , (0,0) X f(x,y) Y

41 ,, "2 f 3 $ "4 4 % % ( x, y) = 0,1,..., L 1 (np. L=256) x y = 0,1,..., N = 0,1,..., M

42 8 4 If each of the colour component is 8 bit coded then 2 24 different colours can be obtained! f ( x, y) = ( f, f, f ) R G B

43 f=25 R G B Monochrome image... Colour palette (look-up table) Colour image

44 * % 2 7 $, " : " " " 7 1 " 7 4 * 7-7 ; 4:. 0 92

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