A novel image/video coding method based on Compressed Sensing theory
2008
Compressed sensing (CS) has been proposed for more efficient signal compression and recovery at theoretical level. This paper proposes a new image/video coding approach combining the CS theory into the traditional discrete cosine transform (DCT) based coding method to achieve better compression efficiency for spatially sparse signal. Furthermore, this new approach is integrated into JPEG and H.264/AVC coding framework as a new coding mode. Rate-distortion optimization is employed for adaptive selection between the new coding mode and the conventional coding modes. Experimental results demonstrated remarkable coding gain for different kinds of natural image/videos by the proposed method.
Keywords:
- Tunstall coding
- Transform coding
- Context-adaptive variable-length coding
- Sub-band coding
- Data compression
- Context-adaptive binary arithmetic coding
- Artificial intelligence
- Computer science
- Theoretical computer science
- Coding tree unit
- Computer vision
- Harmonic Vector Excitation Coding
- Pattern recognition
- Multiview Video Coding
- Correction
- Source
- Cite
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