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Blurring and Local Blurring

Blurring and Local Blurring. 姓名 : 張珮毓 授課教師：張顧耀 教授 報告日期： 2007/06/12. Outline. Introduction Blurring Discrete Gaussian Binomial Blurring Recursive Gaussian IIR Local Blurring. Introduction. This section describes several methods that can be applied to reduce noise on images. Blurring

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Blurring and Local Blurring

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  1. Blurring and Local Blurring 姓名: 張珮毓 授課教師：張顧耀 教授 報告日期：2007/06/12

  2. Outline • Introduction • Blurring • Discrete Gaussian • Binomial Blurring • Recursive Gaussian IIR • Local Blurring

  3. Introduction • This section describes several methods that can be applied to reduce noise on images. • Blurring • Blurring is the traditional approach for removing noise from images. • The effect of blurring on the image spectrum is to attenuate high spatial frequencies.

  4. Outline • Introduction • Blurring • Discrete Gaussian • Binomial Blurring • Recursive Gaussian IIR • Local Blurring

  5. Discrete Gaussian • Header: • #include "itkDiscreteGaussianImageFilter.h" • filter->SetVariance( gaussianVariance ); • filter->SetMaximumKernelWidth( maxKernelWidth );

  6. Discrete Gaussian Effect of the DiscreteGaussianImageFilter on a slice from a MRI proton density image of thebrain.

  7. Discrete Gaussian Variance=3 maxKernelWidth=3*3 Variance=7 maxKernelWidth=3*3

  8. Discrete Gaussian Variance=3 maxKernelWidth=5*5 Variance=3 maxKernelWidth=7*7

  9. Binomial Blurring • Binomial Blurring computes a nearest neighbor average along each dimension • The process is repeated a number of times, as specified by the user.

  10. Binomial Blurring • Binomial filters. 1D versions

  11. Binomial Blurring • In principle, after a large number of iterations the result will approach the convolution with a Gaussian. • Header: • #include "itkBinomialBlurImageFilter.h"

  12. Binomial Blurring Repetitions=2 Repetitions=8

  13. Recursive Gaussian IIR • Finite Impulse Response (FIR) • Infinite Impulse Response (IIR) 只延伸到有限距離(FIR) 延伸到影像邊界(IIR)

  14. Recursive Gaussian IIR • Header: • #include "itkRecursiveGaussianImageFilter.h”

  15. Recursive Gaussian IIR Sigma=3 Sigma=5 Sigma=7

  16. Outline • Introduction • Blurring • Discrete Gaussian • Binomial Blurring • Recursive Gaussian IIR • Local Blurring

  17. Local Blurring • In some cases it is desirable to compute smoothing in restricted regions of the image, or to doit using different parameters that are computed locally.

  18. 參考資料 • ItkSoftwareGuide • http://www.engr.udayton.edu/faculty/jloomis/ece563/notes/filter/smooth/smooth.html • http://ssip2003.info.uvt.ro/lectures/gui/smoothing_techniques_in_image_processing.ppt • http://www.cee.hw.ac.uk/hipr/html/gsmooth.html

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