A Scalable and Adaptive Temporal Segmentation Algorithm for Video Coding

To achieve very low bit-rate transmission, many video coding papers suggest extraction of stationary objects and the background and coding only of moving objects. These techniques, which could seriously distort the output, are mostly applied to spatial domain. A novel scalable adaptive temporal segmentation algorithm for video coding is proposed in this paper. Our proposed algorithm is scalable in terms of compression, quality, and some specific features. A multifunction control of the output is formulated as a cost function, which is flexible enough to implement any desirable criteria, such as channel capacity or reconstruction quality. Our algorithm uses a simple but efficient quantization process instead of using a computationally expensive discontinuity detection. The approach can also be regarded as a combination of adaptive temporal decimation and segmented video coding. The overall bit rate can be regulated according to the user's specifications. Experimental results show that the overall bit rate of video coding can be controlled easily using our scheme. The output quality is good for both subjective and objective tests. We have also found that the size of the time window (N) has significant effects on the quality of the reconstruction, while our proposed algorithm outperforms the adaptive temporal decimation algorithm.