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A comparative study on attention-based rate adaptation for scalable video coding
Conference paper

A comparative study on attention-based rate adaptation for scalable video coding

Chia-Ming Tsai, Chia-Wen Lin, Weisi Lin and Wen-Hsiao Peng
Proceedings - International Conference on Image Processing, ICIP, pp.969-972
2009

Abstract

Perceptual coding Scalable video coding Video adaptation Visual attention model Software Computer Vision and Pattern Recognition Signal Processing
We conduct subjective tests to evaluate the performance of scalable video coding with different spatial-domain bit-allocation methods, visual attention models, and motion feature extractors in the literature. For spatial-domain bit allocation, we use the selective enhancement and quality layer assignment methods. For characterizing visual attention, we use the motion attention model and perceptual quality significant map. For motion features, we adopt motion vectors from hierarchical B-picture coding and optical flow. Experimental results show that a more accurate visual attention model leads to better perceptual quality. In cooperation with a visual attention model, the selective enhancement method, compared to the quality layer assignment, achieves better subjective quality when an ROI has enough bit allocation and its texture is not complex. The quality layer assignment method is suitable for region-wise quality enhancement due to its frame-based allocation nature. ©2009 IEEE.

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