A Two-Step Discrete Cosine Basis Oriented Motion Modeling Approach for Enhanced Motion Compensation.
Summary
This study introduces a new video coding method using discrete cosine basis oriented (DCO) motion modeling to improve efficiency. The approach blends global and local motion information, achieving significant bit rate savings in HEVC and VVC encoders.
Area of Science:
- Digital Signal Processing
- Video Compression
- Computer Vision
Background:
- Video coding relies on minimizing redundancy within sequences.
- Current block-based methods model commonality locally.
- Advanced standards offer improved efficiency over predecessors.
Purpose of the Study:
- To develop a novel commonality modeling approach for video coding.
- To seamlessly blend global and local motion homogeneity information.
- To enhance prediction accuracy and reduce computational complexity.
Main Methods:
- A two-step discrete cosine basis oriented (DCO) motion modeling for frame prediction.
- Utilizing DCO motion models for smooth and sparse representation of complex motion.
- Partitioning frames to investigate conformance to global motion and introducing local DCO models for non-conforming regions.
Main Results:
- Improved rate-distortion performance in a High Efficiency Video Coding (HEVC) encoder.
- Achieved up to 9% bit rate savings by using DCO prediction frames.
- Reported 2.37% bit rate savings when compared to the Versatile Video Coding (VVC) encoder.
Conclusions:
- The proposed method effectively minimizes both global and local motion commonality.
- DCO motion modeling offers advantages over traditional motion models for complex motion.
- This approach enhances video compression efficiency in modern coding standards.
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