1. Yen-Lin Lee and Truong Nguyen ECE Dept., UCSD, La Jolla, CA 92093-0407 Method and Architecture Design for Motion Compensated Frame Interpolation in High-Definition Video Processing

2. Motion compensated frame interpolation (MCFI) Enhance the quality of reconstructed video Work on how to accurately estimate true motions Considers spatial and temporal correlation, searches with block matching algorithm (BMA) proposed method and architecture adopt one-pass and low complexity design

3. The proposed method(1/2) Adopts a motion-compensated approach to insert one or several interpolated frames between any two contiguous original frames

4. The proposed method(2/2) Three major parts: True motion engine Motion estimation, true motion decision, output true MV to interpolator Block-based interpolator obtains motion information performs a motion-compensated procedure with weighted values Deblocking filter Smooth the blocking artifact where a neighboring interpolated block with larger sum of absolute difference (SAD) shows up

5. Bilateral Search Adopt motion re-estimation with bilateral search with original uncompressed frames from a decoder directly seeks two similar blocks from a zero distance of the interpolated block

6. Multi-directional Enlarged Matching Algorithm Larger matching block size could improve the accuracy of searching true motion ( N*N  M*M ) larger part of a particular object is considered. Nine types of enlarged matching directions are defined keep the completeness of the front edge for the moving object.

7. One-pass Process with Multi-grids Classification Simplify the process and reduce the storage size for motion vector field Divides a searching window into multiple areas Each area has one motion candidate.

8. Temporal Object Information One-pass processing would not provide complete info. acquire some temporal information For objects with constant speed, especially in panning scenes. When the camera pans slowly across a scene, most interpolated would move consistently except real moving objects. Remove those inaccurate motion vectors Interpolated blocks with a larger pixel variance are considered, which means that there are more textures.

9. THE PROPOSED ARCHITECTURE white color : functional elements gray color : storage elements

10. True Motion Engine(1/3) it sets nine-grids classification, searching window from -7 to +7 for a down-sampled frame, 8×8 block size, 16×16 enlarged block size, and four candidates for each MSEA sub- block.

11. True Motion Engine(2/3) Multi-level successive eliminate algorithm (MSEA) A fast full-search block matching algorithm (FFSBMA) Following a successive elimination algorithm (SEA) Avoid local trap problem

12. True Motion Engine(3/3) The fourth step : Probable sum of absolute difference (PSAD) MSEA engine decides four highly possible candidates for each directional area PSAD engine only needs to check SAD values for these four vectors instead of a full search with SAD. The fourth step : true motion selection from these nine motion candidates by pre-defines conditions, and neighboring and temporal information. The fifth step : The proposed architecture would perform a refining procedure by probable refining engine (PREF)

13. Implementation double the frame rate for : HDTV1080p (1920×1080) 30fps video at 180MHz HDTV 720p (1280×720) 30fps video at 83MHz the architecture is designed in VHDL and implemented with TSMC 90-nm technology

14. PERFORMANCE AND EXPERIMENTAL RESULT(1/5)

15. PERFORMANCE AND EXPERIMENTAL RESULT(2/5)

16. PERFORMANCE AND EXPERIMENTAL RESULT(3/5)

17. PERFORMANCE AND EXPERIMENTAL RESULT(4/5)

18. PERFORMANCE AND EXPERIMENTAL RESULT(5/5) More result: http://videoprocessing.ucsd.edu/~yenlinlee/mcfi/

19. CONCLUSION The method employs a unique true motion engine with an adaptive overlapped block matching algorithm multi-directional enlarged matching algorithm one-pass process. The proposed architecture employs a modified multi-level successive eliminate algorithm has capabilities to reduce the heavy computation. Experimental results show that the proposed algorithm provides better video quality than conventional methods