gaussian pyramid and its applications
DESCRIPTION
Gaussian Pyramid and Its Applications. Speaker: Po-Hung Wu. Outline. Introduction Gaussian and Laplacian pyramid Application Salient region detection Edge-aware image processing Conclusion Reference. Introduction. Why Gaussian? Easy to implement! A hierarchical way!. Introduction. - PowerPoint PPT PresentationTRANSCRIPT
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Gaussian Pyramid and Its Applications
Speaker: Po-Hung Wu
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Outline Introduction Gaussian and Laplacian pyramid Application
• Salient region detection• Edge-aware image processing
Conclusion Reference
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IntroductionWhy Gaussian?
Easy to implement!
A hierarchical way!
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Introduction What is salient object?
Everyone knows that …..
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Introduction What is edge-aware image processing?
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Gaussian and Laplacian pyramid
g0 : original imagegn : downsample [g(n-1)*G] G : Gaussian filtergn1 : interpolate [gn]Ln = gn – gn1
gn is called Gaussian pyramidLn is called Laplasian pyramid(Use DoG to approximate Laplacian)
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Gaussian and Laplacian pyramid
Synthesis
What’s app? Compression ….Wavelet transform?
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Gaussian and Laplacian pyramid
Hierarchical
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Application Multiresolution interpolation and extrapolation:Taylor series expansion
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Application Multiresolution interpolation and
extrapolation
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Application Image merging
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Application Creating realistic looking images
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App : Salient Region Detection Goals
• well boundary• uniformly highlighted salient region• computational efficiency
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App : Salient Region Detection Alg.1. band-pass filter
2. Saliency map
Iu : mean pixel value Iwhc : image pixel vector in the Gaussian blurred version
2 2 2 2
2 21 2
( ) ( )2 2
2 21 2
1 2
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0
1 1 12
= ( , , ) ( , , )
( , , ) ( , , )
( , , ) ( , , )
x y x y
Nn n
n
N
DoG e e
G x y G x y
G x y G x y
G x y G x y
( , ) || ( , ) ||hcu wS x y I I x y
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App : Salient Region Detection Maximum symmetric surround for
enhancement
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App : Salient Region Detection
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App : Salient Region Detection
What’s drawbacks?› Object not in the middle› (Colorful background)› ….???
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App: edge-aware image processing
What’s edge-aware image processing?
The amplitude of main edges may be increased or reduced, but the edge transitions should not be smoother or sharper.
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App: edge-aware image processing
Signal decomposition in Laplacian pyramid
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App: edge-aware image processing
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App: edge-aware image processing
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App: edge-aware image processing
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App: edge-aware image processing
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App: edge-aware image processing
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App: edge-aware image processing
More example
Input luminance channel RGB channel
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Conclusion Gaussian is powerful. Laplacian pyramids good for edge‐
aware editing Image processing is cool.
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Reference[1] OGDEN, J. M., ADELSON, E. H., BERGEN, J. R., AND BURT, P.
J. Pyramid-Based Computer Graphics. RCA Engineer 30 (1985), 4–15.
[2] PARIS, S., HASINOFF, S.W., AND KAUTZ, J. 2011. Local laplacian filters: Edge-aware image processing with a laplacian pyramid. ACM Trans. Graph..
[3] R. Achanta, S. Hemami, F. Estrada, and S. S¨usstrunk, “Frequency-tuned salient region detection,” IEEE International Conference on Computer Vision and Pattern Recognition, pp. 1597–1604, June 2009.
[4] R. Achanta and S. S¨usstrunk. Saliency detection using maximum symmetric surround. In Proc. of Int’l Conf. on Image Processing (ICIP), 2010.
[5] http://www.csie.ntu.edu.tw/~cyy/ (Pro. Yung-Yu Chuang)
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Thank you for your attention!!!