Multiple Description Coding Method Research Articles

Reliable 3D video streaming considering region of interest

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.

Visual saliency based redundancy allocation in HEVC compatible multiple description video coding

Video delivery over error prone channels suffer from packet loss, which significantly deteriorates the reconstructed video quality. Multiple description coding (MDC) is an effective error resilient coding scheme for transmission of video over unreliable networks, where video is encoded into multiple descriptions having redundancy between them. The amount of redundancy between these descriptions has an important role in MDC, because it provides error resilience. In this paper, a new redundancy allocation scheme using visual saliency model is presented with an aim of achieving high decoding quality, when one or more than one descriptions are received at the decoder. The proposed MDC method splits the input video sequence into even and odd subsequences, which are independently encoded by using high efficiency video coding (HEVC) encoder. The missing frames in each description are predicted by using pixel interpolation and motion interpolation. The residual information is generated by using the interpolated frame and its adjacent frame from the other description, which represents the redundancy in each description. Residual information is encoded based on a visual saliency mask, which is generated using a global contrast based visual saliency model. In this work, two different modes are proposed for visual saliency based redundancy allocation to provide better perceptual quality, while decoding the descriptions. The proposed scheme is implemented on HEVC reference software HM 16.2 and compared with two state-of-the-art temporal subsampling based multiple description video coding methods. Experiments show that the proposed method performs better than the reference methods, both in lossless and packet erasure channel conditions.

Multiple description video coding based on adaptive data reuse

In this paper, an efficient multiple description coding (MDC) method, called the adaptive data reuse MDC (ADR-MDC), is proposed for robust video transmission. The proposed ADR-MDC first groups four sub-sequences, which are generated by performing spatial down-sample operation on each frame of input video sequence, into two descriptions. In each description, one sub-sequence is directly encoded and decoded by applying the H.264/AVC encoder and decoder, while the other is encoded and decoded at each macroblock (MB) based on the adaptive data reuse criterion, which are developed by making full use of the spatial and temporal correlations among the sub-sequences. Experimental results have shown that the proposed ADR-MDC scheme possesses higher error resilient ability and obtains better reconstructed video than the existing state-of-the-art MDC method.

Investigation of Error Concealment Using Different Transform Codings and Multiple Description Codings

Investigation of Error Concealment Using Different Transform Codings and Multiple Description CodingsThere has been increasing usage of Multiple Description Coding (MDC) for error concealment in non-ideal channels. A lot of ideas have been masterminded for MDC method up to now. This paper described the attempts to conceal the error and reconstruct the lost descriptions caused by combining MDC and lapped orthogonal transform (LOT). In this work LOT and other transforms codings (DCT and wavelet) are used to decorrelate the image pixels in the transform domain. LOT has better performance at low bit rates in comparison to DCT and wavelet transform. The results show that MSE for the proposed methods in comparison to DCT and wavelet have decreased significantly. The PSNR values of reconstructed images are high. The subjective evaluation of image is very good and clear. Furthermore, the standard deviations of reconstructed images are very small especially in low capacity channels.

Balanced Multifilter Banks for Multiple Description Coding

The parametrization for one kind of multifilter banks generating balanced multiwavelets is presented in this paper, in which two lowpass filters are flipping filters, and two highpass filters have linear phase. Based on these parametric expressions, some balanced multiwavelets and analysis-ready multiwavelets are constructed, which are symmetric, or antisymmetric. Moreover, on the basis of balanced multiwavelet transform, a new method of multiple description coding is given, and experiments show that this method works well. Compared with the traditional multiple description coding method, this method has low redundancy.

Multiple description wavelet coding with dual decomposition and cross packetization

In this paper, a novel wavelet-based multiple description coding (MDC) is proposed with dual decomposition (DD) and cross packetization (CP). Through dual decomposition, each description has two parts, the primary and the complementary. The former contains the structural information, including the positions and signs of significant coefficients, whereas the latter contains the residual data, which are the absolute values of the significant coefficients’ magnitude. The primary part is most crucial for source reconstruction; hence, their codes generated by the x-tree wavelet encoder are duplicated in both descriptions for heavy protection. On the other hand, the residual data are processed by the multiple description scalar quantizer to generate two indices for their respective descriptions as the complementary part. The proposed DD–MDC method effectively enhances error-resilience capability for robust transmission. For the packet-switching networks, the proposed CP, which produces the row packets and column packets for the two descriptions, respectively, is incorporated into the DD–MDC framework, leading to the DDCP–MDC scheme. Extensive simulation results have clearly shown that the proposed wavelet-based DD–MDC and DDCP–MDC methods are highly error resilient and consistently yield high coding gain; particularly, when only one description is available, the reconstructed image quality is superior to that obtained with other existing methods.

Distributed video streaming using multiple description coding and unequal error protection

This paper presents a distributed video streaming framework using unbalanced multiple description coding (MDC) and unequal error protection. In the proposed video streaming framework, two senders simultaneously stream complementary descriptions to a single receiver over different paths. To minimize the overall distortion and exploit the benefits of multipath transport when the characteristics of each path are different, an unbalanced MDC method for wavelet-based coders combined with a TCP-friendly rate allocation algorithm is proposed. The proposed rate allocation algorithm adjusts the transmission rates and the channel coding rates for all senders in a coordinated fashion to minimize the overall distortion. Simulation results show that the proposed unbalanced MDC combined with our rate allocation algorithm achieves about 1-6 dB higher peal signal-to-noise ratio compared to conventional balanced MDC when the available bandwidths along the two paths are different under time-varying network conditions.