Implementation of Optimized Diamond Search                                 Algorithm           A Term Project for the cour...
Motion Estimation is one of themost time consuming part invideo encoding system, it is aprocess of determining motionvecto...
   Full Search (FS)   Binary Search (BS)   Three Step Search (TSS)   Four Step Search (FSS)   Diamond Search (DS)    ...
Step 1: Let say center point is(x,y)    and      having    eightneighborhood points. ComputeSAD      (Sum       of   Absol...
Figure 3. Flow Chart of DS Algorithm                                       5
3    3SAD =  I ( x  k , y  l )  S (k , l )          k 0 l 0                      X – Y, X >Y  |X–Y|     =         Y...
(x,y-1)(x-1,y)                              (x+1,y)              (x,y)          (x,y+1)                    Figure 4. SAD C...
8
9
10
Questions???               11
Upcoming SlideShare
Loading in …5
×

Implementation of optimized diamond search algorithm

767 views

Published on

Published in: Technology, Business
0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
767
On SlideShare
0
From Embeds
0
Number of Embeds
3
Actions
Shares
0
Downloads
0
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

Implementation of optimized diamond search algorithm

  1. 1. Implementation of Optimized Diamond Search Algorithm A Term Project for the course of Advance Digital System Design By Muhammad Naeem Tayyab Supervisor: Dr. Rehan Hafiz 1
  2. 2. Motion Estimation is one of themost time consuming part invideo encoding system, it is aprocess of determining motionvectors that describestransformations from one imageto another.Block Matching is the way oflocating matching blocks in asequence of digital video Figure 1. Block Matchingframes for the purpose ofMotion Estimation. 2
  3. 3.  Full Search (FS) Binary Search (BS) Three Step Search (TSS) Four Step Search (FSS) Diamond Search (DS) 3
  4. 4. Step 1: Let say center point is(x,y) and having eightneighborhood points. ComputeSAD (Sum of AbsoluteDifference) at four points(x+1,y), (x-1,y),(x,y+1) and (x,y-1). New point is the one havingminimum SAD value.Step 2: Keep doing Step 1 untilyou found MinSAD at centerpoint. Figure 2. Example of DS Algorithm 4
  5. 5. Figure 3. Flow Chart of DS Algorithm 5
  6. 6. 3 3SAD =  I ( x  k , y  l )  S (k , l ) k 0 l 0 X – Y, X >Y |X–Y| = Y – X, Y >X 0, X == Y 6
  7. 7. (x,y-1)(x-1,y) (x+1,y) (x,y) (x,y+1) Figure 4. SAD Calculation Points 7
  8. 8. 8
  9. 9. 9
  10. 10. 10
  11. 11. Questions??? 11

×