Scalable Video Coding with Compressive Sensing for Wireless Videocast

Channel coding such as Reed-Solomon (RS) and convolutional codes has been widely used to protect video transmission in wireless networks. However, this type of channel coding can effectively correct error bits only if the error rate is smaller than a given threshold; when the bit error rate is underestimated, the effectiveness of channel coding drops dramatically and so does the decoded video quality. In this paper, we propose a low-complex, scalable video coding architecture based on compressive sensing (SVCCS) for wireless unicast and multicast transmissions. SVCCS achieves good scalability, error resilience and coding efficiency. SVCCS encoded bitstream is divided into base and enhancement layer. The layered structure provides quality and temporal scalability. While in the enhancement layer, the CS measurements provide fine granular quality scalability. In addition, we incorporate state-of-the-art technologies of compressive sensing to improve the coding efficiency. Experimental results show that SVCCS is more effective and efficient for wireless videocast than the existing solutions.