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Digital Image Processing ECE.09.452/ECE.09.552 Fall 2007

Digital Image Processing ECE.09.452/ECE.09.552 Fall 2007. Lecture 6 October 29, 2007. Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/fall07/dip/. Plan. Digital Image Restoration Recall: Environmental Models Image Degradation Model

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Digital Image Processing ECE.09.452/ECE.09.552 Fall 2007

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  1. Digital Image ProcessingECE.09.452/ECE.09.552Fall 2007 Lecture 6October 29, 2007 Shreekanth Mandayam ECE Department Rowan University http://engineering.rowan.edu/~shreek/fall07/dip/

  2. Plan • Digital Image Restoration • Recall: Environmental Models • Image Degradation Model • Image Restoration Model • Point Spread Function (PSF) Models • Linear Algebraic Restoration • Unconstrained (Inverse Filter, Pseudoinverse Filter) • Constrained (Wiener Filter, Kalman Filter) • Lab 3: Digital Image Restoration

  3. DIP: Details

  4. Image Preprocessing Restoration Enhancement • Inverse filtering • Wiener filtering Spectral Domain Spatial Domain • Filtering • >>fft2/ifft2 • >>fftshift • Point Processing • >>imadjust • >>histeq • Spatial filtering • >>filter2

  5. “Better” visual representation Subjective No quantitative measures Remove effects of sensing environment Objective Mathematical, model dependent quantitative measures Enhancement vs. Restoration

  6. S f(x,y) g(x,y) h(x,y) n(x,y) Degradation Model: g = h*f + n Degradation Model • demos/demo5blur_invfilter/ • demos/demo5blur_invfilter/degrade.m

  7. Restoration Model Degradation Model Restoration Filter f(x,y) f(x,y) Unconstrained Constrained • Inverse Filter • Pseudo-inverse Filter • Wiener Filter • demos/demo5blur_invfilter/

  8. f(x,y) Build degradation model f(x,y) Analyze using algebraic techniques Formulate restoration algorithms Implement using Fourier transforms Approach g = h*f + n g = Hf + n W -1g = DW -1f + W -1n f = H -1g F(u,v) = G(u,v)/H(u,v) • demos/demo5blur_invfilter/

  9. Degradation & Restoration Examples: Gonzalez & Woods Atmospheric Turbulence Model

  10. Degradation & Restoration Examples: Gonzalez & Woods Example 5.11: Inverse Filtering

  11. Degradation & Restoration Examples: Gonzalez & Woods Example 5.12: Wiener Filtering

  12. Degradation & Restoration Examples: Gonzalez & Woods Example 5.10: Planar Motion Model

  13. Degradation & Restoration Examples: Gonzalez & Woods Example 5.13: Inverse and Wiener Filtering

  14. Lab 3: Digital Image Restoration http://engineering.rowan.edu/~shreek/fall07/dip/lab3.html

  15. Summary

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