branxton
Uploaded by
18 SLIDES
367 VUES
190LIKES

Blurring and Local Blurring

DESCRIPTION

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

1 / 18

Télécharger la présentation

Blurring and Local Blurring

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  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

More Related