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Elements of Biomedical Image Processing BMI 731 Winter 2005

Elements of Biomedical Image Processing BMI 731 Winter 2005. Kun Huang Department of Biomedical Informatics Ohio State University. Introduction to imaging processing Mathematical background Convolution and Fourier transform Filtering Image enhancement Noise removal

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Elements of Biomedical Image Processing BMI 731 Winter 2005

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  1. Elements of Biomedical Image ProcessingBMI 731 Winter 2005 Kun Huang Department of Biomedical Informatics Ohio State University

  2. Introduction to imaging processing • Mathematical background • Convolution and Fourier transform • Filtering • Image enhancement • Noise removal • Color correction and color space transform • Feature extraction • Edge, point, line (Hugh transform) • 3-D reconstruction • Radon transform

  3. Image Processing : what should be done? • Image restoration and enhancement • Feature extraction • Pattern recognition

  4. 1x2+8x9+15x4+7x7+14x5 +16x3+13x6+20x1+22x8 =575 • Mathematical Background • Convolution • 2-D convolution

  5. Mathematical Background • Fourier transform (FT) • Mathematics • 2-D FT

  6. Mathematical Background • Fourier transform (FT) • Fast FT (FFT)

  7. Mathematical Background • Convolution and Fourier transform (FT)

  8. Mathematical Background • Filtering • High-pass filter, low-pass filter, band pass filter • Gradient filters

  9. Mathematical Background • Filtering • Wiener filter and deblurring

  10. 43 • Image Enhancement • Denoise • Averaging • Median filter

  11. Image Enhancement • Denoise/restoration From Gonzalez, Woods, and Eddins

  12. Image Enhancement • Color and intensity adjustment • Histogram equalization

  13. RGB -> HSV, HSL, YCbCr, … R = 64 G = 31 B = 62 R = 125 G = 80 B = 147 H = 214 S = 132 V = 64 H = 199 S = 117 V = 147 • Image Enhancement • Color space transform

  14. Feature Extraction • Region detection – morphology manipulation • Dilate and Erode • Open • Erode  dilate • Small objects are removed • Close • Dilate  Erode • Holes are closed • Skeleton and perimeter

  15. Feature Extraction • Edge detection • Gradients • Canny edge detector • Gaussian smoothing • Gradients • Two thresholds • Thinning

  16. x • Feature Extraction • Point detection • Harris detector

  17. y q y q • Feature Extraction • Radon transform • Straight line detection • Hugh transform

  18. From Gonzalez, Woods, and Eddins • Feature Extraction • Straight line detection • Hugh transform

  19. 2-D/3-D reconstruction • Radon/inverse radon transforms and backprojection

  20. Reference • Digital Image Processing using Matlab By R.C.Gonzalez, R.E.Woods, and S.L.Eddins Published by Printice-Hall, 2004

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