Depth-Based Multiview Distributed Video Coding

Abstract

Multiview distributed video coding (DVC) has gained much attention in the last few years because of its potential in avoiding communication between cameras without decreasing the coding performance. However, the current results are not matching the expectations mainly due to the fact that some theoretical assumptions are not satisfied in the current implementations. For example, in distributed source coding the encoder must know the correlation between the sources, which cannot be achieved in the traditional DVC systems without having a communication between the cameras. In this work, we propose a novel multiview distributed video coding scheme in which the depth maps are used to estimate the way two views are correlated with no exchanges between the cameras. Only their relative positions are known. We design the complete scheme and further propose a rate allocation algorithm to efficiently share the bit budget between the different components of our scheme. Then, a rate allocation algorithm for depth maps is proposed in order to maximize the quality of synthesized virtual views. We show, through detailed experiments, that our scheme significantly outperforms the state-of-the-art DVC system. Index Terms-3DTV, depth image based rendering (DIBR), depth maps, distributed source coding, shape adaptive coding.

Source Symbol Purging-Based Distributed Conditional Arithmetic Coding

“…It is difficult to fairly compare the cumulative product of posterior probabilities in different paths, since the calculation of P(X i =x i |X i−1 i−k =x i−1 i−k , CX i ) depends on the occurrence of decoding ambiguity. If the decoder of DAC use (5) to calculate the posterior probability, the cumulative product of posterior probabilities of a decoding path with many ambiguities will be much smaller than that of another decoding path with a few ambiguities. Apparently, such a difference between the cumulative product of posterior probabilities is not caused by the different correlations between the corresponding decoding sequences and the side information sequence.…”

“…DSC is based on two important theorems: the first is the Slepian-Wolf theorem [1], which proves that when data is losslessly compressed, independent coding and joint coding of related sources are equally effective; the second is the Wyner-Ziv theorem [2], which establishes the foundation for lossy DSC schemes. Today, DSC has led to achievements in many practical applications, such as: distributed video coding [3], hyperspectral image compression [4], multi-view video coding [5], wireless sensor network communication [6], image authentication [7], biometric information recognition [8] and so on.…”

A Novel Segmentation Based Depth Map Up-Sampling

“…Index Terms-image segmentation, SLIC, region-growing, region merging, joint trilateral filtering I. INTRODUCTION 3 D visual technologies have been widely used in multiple applications currently, such as free-viewpoint television (FTV), 3D games, 3D virtual video conference, human computer interaction and so on [1][2][3][4] [5] [6]. Accurate and high-resolution (HR) depth acquisition is one of the most crucial issues in lots of 3D visual technologies, which has attracted great attentions of many researchers.…”