Bit-stream extraction to maximize perceptual quality using quality information table in SVC

In scalable video coding (SVC), video quality can be controlled by bit-stream extraction. The bit-stream extraction is to extract network abstraction layer (NAL) units for the required quality. Since scalable bit-stream is packed in NAL units, quality control of SVC video is highly related to NAL unit extraction policy at a given bit-rate. Therefore, effective extraction policy is required to provide SVC video with optimal quality. In this paper, a SVC bit-stream extraction method based on perceptual quality is proposed. The main goal of this work is to find the optimal extraction policy for SVC bit-stream that contain the spatial, temporal, and SNR scalability at a given bit-rate. Also, to consider perceptual quality relied on video characteristics, the video segments are classified into different classes, namely action, crowd, dialog, scenery, and text&graphic. As a result of a subjective test on the classified video scenes, consistent characteristic of perceptual quality preference is achieved. Based on this, quality information table (QIT) has been determined for each class which guides the bit-stream extraction process. The determined QIT is applied to SVC bit-stream extraction depending on to which class a video segment belongs. In the experiment, the proposed extraction scheme is applied for SVC bit-stream extraction belongs to action class. Extraction policy to maximize perceptual quality of action class is applied based on QIT for action class. The extracted video and multi-dimensional scalability resulted from the proposed scheme are also described.