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Video Communication Final project

Video Communication Final project. 宋翊誠 M983010047 電機碩 2. outline. Introduce My method Vedio demo Compare Conclusion R eference. Introduce(1/5). First idea ： It is from diamond search , I use the ” hexagon ” instead of the shape of the diamond.

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Video Communication Final project

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  1. Video Communication Final project 宋翊誠 M983010047 電機碩2

  2. outline • Introduce • My method • Vedio demo • Compare • Conclusion • Reference

  3. Introduce(1/5) • First idea ：It is from diamond search , I use the”hexagon”instead of the shape of the diamond. • Result of first idea ： The method already be published in a paper[1].

  4. Introduce(2/5) • Large Cellular Search Pattern(LCSP)[1]：

  5. Introduce(3/5) • Second idea： To find the disadvantage of the LCSP search . I think it have two cases that we can improve the method. • The point which has the smallest SAD is in the central of the hexagon.Compare wit the Diamond search [2] , the search points of central are too much. • The point which has the smallest SAD is not in the central range of the hexagon. it maybe cost many search times to find it.

  6. Introduce(4/5) • Case one :

  7. Introduce(5/5) • Case two ：

  8. My method(1/6) • Improve ： • For first case , we record the point which has the second small SAD , and reduce the search point from 8 to 2or 3 . • For second case , we seta boundary and check whether the point of smallest SAD that we can find is over the boundary or not .Then we dynamic alignment the size of the hexagon .

  9. My method(2/6) • For case one: Smallest SAD is in the central of the hexagon

  10. My method(3/6) • Step1:When the point of the smallest SAD is in the central of the hexagon , we compare with the SAD value of the other 6 points • Step2 : Find the point of the second smallest SAD value . • Step 3 : According to the smallest one and the second smallest one that we can just search the points in the range between these two points.

  11. My method(4/6) • For case two：Smallest SAD is not in the central of the hexagon.

  12. My method(5/6) • Step1 : At first , we just use the small size of the hexagon to do the search , when it finish the search in this MB , we record the seat of the point of the smallest SAD. • Step 2 : We set the search window size (+-4 , +-4 ) to be a boundary , and we check whether the seat of the point of the smallest SAD appear over the boundary two times Continuously or not .If it is ,we add the size of hexagon to be double.

  13. My method(6/6) • Step 3: If the size of hexagon is double , when the point of the smallest SAD is in the central of the hexagon .Then next search , we reduce the size to be half and do the search in the small size of the hexagon. • Step 4 : When we check whether the seat of the point of the smallest SAD appear in the boundary two times Continuously or not .If it is , we reduce the size of hexagon to be half ,and go to Step 1.

  14. Vedio demo(1/7) • Full search • Large Cellular Search Pattern • My method

  15. FULL search Vedio demo(2/7) Original Full search

  16. Vediodemo(3/7) • Large Cellular Search Pattern Original LCSP search

  17. Vediodemo(4/7) • My method Original My method search

  18. Vediodemo(5/7) • Full search Original Full search

  19. Vediodemo(6/7) • Large Cellular Search Pattern Original LCSP search

  20. Vediodemo(7/7) • My method Original My method search

  21. Compare(1/4) • Average PSNR • Akiyo

  22. Compare(2/4) PSNR Frame no.

  23. Compare(3/4) 2) Football

  24. Compare(4/4) PSNR Frame no.

  25. Conclusion • The search times of My method can better than the Full search and the LCSP serch. • The PSNR of My method is not better than Full search and the LCSP search. • My method maybe can reduce the search times , but it can not improve the PSNR.

  26. Reference • [1] JEANSON HUNG, HUNG-SHUNG WONG , and JUNG-HUA WANG, “ A Novel search Algorithm for Block-Matching Motion Estimation ”http://softcomp.ee.ntou.edu.tw/publications/conference/novel_cellular.pdf • [2] J. Y. Tham, S. Ranganath, M. Ranganath, and A. A. Kassim, “A Novel Unrestricted Center-Biased Diamond Search Algorithm for Block Motion Estimation,” IEEE Trans. Circuits Syst. Video Technol., vol. 8, No. 4, pp. 369-377, Aug. 1998 http://www.cesca.centers.vt.edu/research/references/video/Motion_Estimation/Tham98a.pdf

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