A video bit allocation technique adopting a visual distortion sensitivity model for better rate-visual distortion coding control is proposed in this paper. Instead of applying complicated semantic understanding, the proposed automatic distortion sensitivity analysis process analyzes both the motion and the texture structures in the video sequences in order to achieve better bit allocation for rate-constrained video coding. The proposed technique evaluates the perceptual distortion sensitivity on a macroblock basis, and allocates fewer bits to regions permitting large perceptual distortions for rate reduction. The proposed algorithm can be incorporated into existing video coding rate control schemes to achieve same visual quality at reduced bitrate. Experiments based on H.264 JM7.6 show that this technique achieves bit-rate saving of up to 40.61%. However, the conducted subjective viewing experiments show that there is no perceptual quality degradation. EDICS - 1-CPRS, 3-QUAL.
- Bit allocation
- Psychovisual model
- Rate-visual distortion analysis
- Visual attention
- Visual masking