1.  Introduction  Gaussian and Laplacian pyramid  Application Salient region detection Edge-aware image processing  Conclusion  Reference 2.

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Presentation transcript:

1

 Introduction  Gaussian and Laplacian pyramid  Application Salient region detection Edge-aware image processing  Conclusion  Reference 2

Why Gaussian?  Easy to implement!  A hierarchical way! 3

 What is salient object? Everyone knows that ….. 4

 What is edge-aware image processing? 5

g 0 : original image g n : downsample [g (n-1)* G] G : Gaussian filter g n1 : interpolate [g n ] L n = g n – g n1 g n is called Gaussian pyramid L n is called Laplasian pyramid (Use DoG to approximate Laplacian) 6

 Synthesis  What’s app? Compression ….Wavelet transform? 7

 Hierarchical 8

 Multiresolution interpolation and extrapolation: Taylor series expansion 9

 Multiresolution interpolation and extrapolation 10

 Image merging 11

 Creating realistic looking images 12

 Goals well boundary uniformly highlighted salient region computational efficiency 13

 Alg. 1. band-pass filter 2. Saliency map I u : mean pixel value I w hc : image pixel vector in the Gaussian blurred version 14

 Maximum symmetric surround for enhancement 15

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 What’s drawbacks? › Object not in the middle › (Colorful background) › ….??? 17

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. 18

 Signal decomposition in Laplacian pyramid 19

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 More example 25 Input luminance channel RGB channel

 Gaussian is powerful.  Laplacian pyramids good for edge ‐ aware editing  Image processing is cool. 26

[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 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 [4] R. Achanta and S. S¨usstrunk. Saliency detection using maximum symmetric surround. In Proc. of Int’l Conf. on Image Processing (ICIP), [5] (Pro. Yung-Yu Chuang) 27

Thank you for your attention!!! 28