Abstract
3D video applications are growing more common as communication technology becomes more predominant nowadays. With such increasing demand for the 3D multimedia services in either the wired or wireless networks, robust methods of video streaming will be introduced to show more favorable efficiency outcomes since packet failure is an integral characteristic of communication networks.This paper aims to introduce a new reliable method of stereoscopic video streaming based on multiple description coding (MDC) strategy. The proposed multiple description coding generates four 3D video descriptions considering the interesting objects contained in the scene. To be able to find the interesting objects in the scene, we use two metrics from the second-order statistics of the depth map image in a block-wise manner. Having detected the objects, the proposed multiple description coding algorithm generates the descriptions for the color video using a nonidentical decimation method with respect to the identified objects. To show how much reliable the proposed MDC method is, this article assumes that due to the unreliable communication channel, only one description, among four encoded descriptions, is delivered to the receiver successfully. Therefore, the receiver needs to estimate the missed descriptions’ data from the available description. Since the human eye is more sensitive to objects than it is to pixels, the proposed method provides a better visual performance in view of its subjective assessment. Although, the objective test results verify the fact that the proposed method provides an improved performance than the Polyphase SubSampling (PSS) multiple description coding and our previous work using pixel variation. Regarding the depth map image, the proposed method generates the multiple descriptions according to the pixel prediction difficulty level. The considerable improvement achieved by the proposed method is shown with the peak signal-to-noise ratio (PSNR) and Structural SIMilarity (SSIM) simulation result.
Highlights
Even though the technology for producing memory has been developed in the last decade, it is still a challenge to save the enormous volume of Three dimensional (3D)/multiview video data effectively
Errors can occur due to packet loss, corruption, congestion, and large packet delay, whereas in the wireless networks, unreliable communication can stem from temperature noise and interference that exist in the physical environment
4 Conclusions Multimedia streaming is affected by packet failure in the network due to packet loss, packet corruption, and large packet delay
Summary
Multimedia communications such as broadcast TV, TV on demand, video conference, and live stream event services have grown exponentially over the last few years making it difficult for operators to keep up with the increasing demand for bandwidth capacity for streamlining videos; with the advent of High-Efficiency Video Coding (HEVC) and the later video streaming algorithms such as parallel framework on many-core processors presented in [1, 2], the major pace to deliver high-definition (HD) video to consumers has been done. The hierarchical block division algorithm needs more time to identify different regions in the frame Another suggestion is to use the ROI map extracted from the depth map image to focus on region II for the enhancement of pixel resolution in the color video frame rather than on region III which is performed within the depth map stream. It should be mentioned that since the human eye is more sensitive to objects rather than pixels, a subjective assessment can better emphasize the improved performance brought forward by the proposed algorithm compared to the previous methods When it comes to the evaluation of the proposed algorithm for the reconstructed depth map image, it shows a better performance. To implement H.265/HEVC encoder, we used H.265 reference software, HM 6.0 [26]
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