Scalable H.264 Wireless Video Transmission over MIMO-OFDM Channels

Abstract. A cross-layer optimization scheme is proposed for scalable video transmission over wireless Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems. The scalable video coding (SVC) extension of H.264/AVC is used for video source coding. The proposed cross-layer optimization scheme jointly optimizes application layer parameters and physical layer parameters. The objective is to minimize the expected video distortion at the receiver. Two methods have been developed for the estimation of video distortion at the receiver, which is essential for the cross-layer optimization. In addition, two different priority mappings of the SVC scalable layers are considered. Experimental results are provided and conclusions are drawn

A Rate-Distortion Optimal Hybrid Scalable/Multiple-Description Video Codec

In this paper, we present a rate-distortion optimal hybrid scalable/multiple-description video codec. Traditional scalable codecs produce bitstreams which can be partitioned into layers that form a hierarchy. Thus, in order for a particular layer to be useful to the decoder, all hierarchically higher layers also need to be available. Conversely, traditional multiple description codecs produce layers with no hierarchy. Thus, any of the layers can be decoded by itself and produce a video sequence of a certain quality. The more layers are available to the decoder, the better the corresponding video quality. The drawback of multiple description coding is that layers need to be correlated at the expense of compression efficiency. We propose a hybrid scalable/multiple description codec which produces a base layer and two multiple description enhancement layers. The base layer is required for decoding. If one or two of the multiple description enhancement layers are also received, the SNR of the received video sequence is improved. There is no hierarchy in the multiple description enhancement layers. The layers are constructed using a rate-distortion optimal partitioning of the DCT coefficients. Experimental results are presented and conclusions are drawn

Quality Variation Control for Three-Dimensional Wavelet-Based Video Coders

The fluctuation of quality in time is a problem that exists in motion-compensated-temporal-filtering (MCTF-) based video coding. The goal of this paper is to design a solution for overcoming the distortion fluctuation challenges faced by wavelet-based video coders. We propose a new technique for determining the number of bits to be allocated to each temporal subband in order to minimize the fluctuation in the quality of the reconstructed video. Also, the wavelet filter properties are explored to design suitable scaling coefficients with the objective of smoothening the temporal PSNR. The biorthogonal 5/3 wavelet filter is considered in this paper and experimental results are presented for 2D+t and t+2D MCTF wavelet coders

Choice Of Threshold Of The Huber-Markov Prior In Map-Based Video Resolution Enhancement

MAP (Maximum A Posteriori) -based resolution enhancement technique with Huber-Markov random field (HMRF) as the image prior has been proposed in the literature, and better preserves image discontinuities when compared with a Gaussian prior model. The reconstruction relies on the choice of Huber function parameter, or threshold T. There is no explicit selection of T in the previous studies. In this paper, we propose a method for choosing the threshold of the HMRF image prior in MAP based resolution enhancement. The method is based on the fact that the threshold T of the Huber function in the HMRF image priors is physically the trade-off between high-frequency components and lowfrequency components for imagery data. High-pass filtering using the discrete Laplacian kernel along with the Huber function is used as the smoothness measure. When the high-passed value is less than T, the measure is a parabola function, while when the value is larger than T, the smoothness measure becomes a linear function. We hence define two different sets and derive the MAP estimator as a function of T. Experimental results are presented and conclusions are drawn

Optimal power allocation and joint source–channel coding for wireless DS-CDMA visual sensor networks using the Nash bargaining solution

ABSTRACT In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network