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Modeling Speckle Noise Using MATLAB

Modeling Speckle Noise Using MATLAB. Adam Baldoni , Dickinson College Mentor: Dr. Ilker Kocyigit , Dartmouth College. What is speckle?. Noise phenomenon that occurs in imaging. Why is speckle important?. Ultrasound SAR. Where does speckle come from?.

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Modeling Speckle Noise Using MATLAB

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  1. Modeling Speckle Noise Using MATLAB Adam Baldoni, Dickinson College Mentor: Dr. IlkerKocyigit, Dartmouth College

  2. What is speckle? • Noise phenomenon that occurs in imaging

  3. Why is speckle important? • Ultrasound • SAR

  4. Where does speckle come from? • Approximating a surface with a reflectivity array • In reality, many scatterers in resolution cell • Causes constructive and destructive interference

  5. How do we model speckle? • Multiplicative noise based on Rayleigh distribution • Take away scatterer assumptions • Many weak reflectors vs 1 strong representative scatterer

  6. Basic Idea Sensor Array Sources/Object a L

  7. Born Approximation and Kirchhoff Migration Born Approx: Discretization: Kirchhoff Migration:

  8. Resolutions and Scaling Cross Range Resolution: Range Resolution:

  9. Building the code • First version of code assumes a strong reflector located at the center of the pixel • Second version assumes many weak reflectors located anywhere within pixel (speckle)

  10. Original Image

  11. First Version

  12. Second Version (speckled)

  13. Second Version #2

  14. Obtaining statistical stability • Current version of code is not statistically stable • Technique available to increase stability • Technique causes some resolution loss

  15. Statistical Stability Technique

  16. Moving Forward • Implement self-averaging technique • Improve code efficiency • Use code to research gaining information from speckle of different objects

  17. Acknowledgements • Dr. Anne Gelb • Dr. Feng Fu • Tracy Moloney • Dr. IlkerKocyigit • REU students • Dartmouth College

  18. Single vs Multiple Frequency Imaging • Single Frequency • Uses a single central frequency • Computationally less expensive • Noisy • Multiple Frequency • Uses multiple frequencies within bandwidth • Background noise cancels out • Computationally expensive

  19. Single Frequency

  20. Multiple Frequency

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