Joint Texture/Depth Power Allocation for 3-D Video SoftCast

You are here

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

Joint Texture/Depth Power Allocation for 3-D Video SoftCast

By: 
Lei Luo; Taihai Yang; Ce Zhu; Zhi Jin; Shu Tang;

Recently, a novel uncoded (pseudoanalog) scheme called SoftCast is proposed for wireless video transmission, which eliminates the cliff effect of the state-of-the-art source-channel coding based schemes and achieves linear quality transition within a wide range of channel signal-to-noise ratio. Therefore, SoftCast-like uncoded and hybrid transmission has become an attractive research issue for natural 2-D video. However, very few studies focus on the SoftCast-based wireless transmission of the 3-D video (3DV) currently. One critical issue of 3DV SoftCast is how to allocate the limited power budget of the transmitter to the texture videos and depth maps of the 3DV to achieve the optimal overall quality on the receiver side, including the transmission quality of the reference views and the synthesis quality of the virtual views. This paper attempts to solve the optimal joint power allocation problem in an efficient way. First, we formulate the target problem as a constrained power-distortion optimization (PDO) problem mathematically. Then, each part of the distortion is analyzed and formulated in a closed form. Finally, the PDO problem is mapped to an unconstrained convex optimization problem and solved by the Lagrangian multiplier method. Simulation results demonstrate that the performance of the proposed method is close to that of the full search method, which can provide the best performance theoretically. Nevertheless, the complexity of the proposed method is negligible compared with that of the full search method. In addition, as compared with the fixed ratio (e.g., 1:1) power allocation between texture and depth, the proposed method can achieve a PNSR gain up to 1.8 dB.

SPS on Twitter

SPS Videos


Signal Processing in Home Assistants

 


Multimedia Forensics


Careers in Signal Processing             

 


Under the Radar