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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. Yen-Lin Lee and Truong Nguyen ECE Dept., UCSD, La Jolla, CA 92093-0407. Motion compensated frame interpolation (MCFI). Enhance the quality of reconstructed video

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Yen-Lin Lee and Truong Nguyen ECE Dept., UCSD, La Jolla, CA 92093-0407

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

  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 • HDTV720p (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

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