Maja Bystrom

Low-complexity skip prediction for H.264 through Lagrangian cost estimation

A complexity reduction algorithm for an H.264 encoder is proposed. Computational savings are achieved by identifying, prior to motion estimation, macroblocks (MBs) that are likely to be skipped and hence saving further computational processing of these MBs. This early prediction is made by estimating a Lagrangian rate-distortion cost function which incorporates an adaptive model for the Lagrange multiplier parameter based on local sequence statistics. Simulation results demonstrate that the algorithm can achieve computational savings of 19%-67% (depending on the source sequence) with no significant loss of rate-distortion performance.

Combined source-channel coding schemes for video transmission over an additive white Gaussian noise channel

There has been an increased interest in the transmission of digital video over real-world transmission media, such as the direct broadcast satellite (DBS) channel. Video transmitted over such a channel is subject to degradation due, in part, to additive white Gaussian noise (AWGN). Some form of forward error-control (FEC) coding may be applied in order to reduce the effect of the noise on the transmitted bitstream; however, determination of the appropriate level of FEC coding is generally an unwieldy and computationally intensive problem, as it may depend upon a variety of parameters such as the type of video, the available bandwidth, and the channel SNR. More specifically, a combined source-channel coding approach is necessary in optimally allocating rate between source and channel coding subject to a fixed constraint on overall transmission bandwidth. In this paper we develop a method of optimal bit allocation under the assumption that the distortion is additive and independent on a frame-by-frame basis. A set of universal operational distortion-rate characteristics is developed which balances the tradeoff between source coding accuracy and channel error protection for a fixed overall transmission rate and provides the basis for the optimal bit allocation approach. The results for specific source and channel coding schemes show marked improvement over suboptimum choices of channel error protection. In addition, we show that our results approach information-theoretic performance bounds which are developed in this work.

H.264/AVC data partitioning for mobile video communication

In this work we compare nonscalable video coding with data partitioning using H.264/AVC under similar application and channel constraints for conversational applications over mobile channels. For both systems optimized rate allocation and network feedback has been applied. From the experimental results it is observed that based on the average PSNR the nonscalable system outperforms the data partitioning system. However, with the data partitioning system the percentage of entirely lost frames can be lowered, and the probability of poor quality decoded video can be reduced.

Soft source decoding with applications

Motivated by previous results in joint source-channel coding and decoding, we consider the problem of decoding of variable-length codes using soft channel values. We present results of decoding of selected codes using the maximum a posteriori (MAP) decoder and the sequential decoder, and show the performance gains over decoding using hard decisions alone. The objective behind this work is to provide motivation for decoding of data compressed by standard source coding schemes, that is, to view the compressed bitstreams as being the output of variable-length coders and to make use of the redundancy in the bitstreams to assist in decoding. In order to illustrate the performance achievable by soft decoding, we provide results for decoding of MPEG-4 reversible variable-length codes as well as for decoding of MPEG-4 overhead information, under the assumption that this information is transmitted without channel coding over an additive white Gaussian noise channel. Finally, we present a method of unequal error protection for an MPEG-4 bitstream using the MAP and sequential source decoders, and show results comparable to those achievable by serial application of source and channel coding.

Soft decoding of variable-length codes

We present the results of two methods for soft decoding of variable-length codes. We first show that maximum likelihood (ML) sequential decoding and maximum a posteriori (MAP) sequence estimation gives significant decoding improvements over hard decisions alone, then we show that further improvements can be gained by additional transmission of the symbol length. Finally, we show that it is possible to make use of the inherent meaning of the codewords without additional transmission of side information which results in a further gain.

Dependent source and channel rate allocation for video transmission

A general joint source-channel rate allocation scheme for a dependent video coding environment is presented. It is assumed that the source coders rely on motion-compensated prediction, and thus error propagation will contribute significantly to the degradation of the reconstructed video. The rate allocation methodology is based upon generation of operational distortion-rate characteristics. In order to reduce computational complexity, these surfaces and the channel code performance are modeled. An analytic method for computing optimal rate allocation across frames in a video sequence is then introduced. Comparisons are made between equal error protection and unequal error protection over video frames. Results are shown for H.263 compressed video used in conjunction with rate-compatible punctured convolutional codes.

Hybrid error concealment schemes for broadcast video transmission over ATM networks

Two hybrid error concealment schemes based on application of forward error control (FEC) coding in combination with passive error concealment techniques to different layers of coded data in a video transmission system are evaluated. It is shown that use of passive error concealment schemes alone generally does not provide sufficient protection against channel errors, especially in the case of video sequences with significant motion or scene changes. Motivated by these observations, a third hybrid scheme is introduced; this scheme involves adaptive application of FEC codes to high-priority information depending on the level of motion in a sequence. It is shown that through application of this adaptive motion-based scheme, significant savings in bandwidth may be obtained at the expense of only a negligible decrease in reconstructed image quality. Implementation of adaptive motion-based FEC coding in a multiresolution asynchronous transfer mode framework is discussed, and metrics for computing motion in both a subband and an MPEG-2 coding system are introduced.

Complexity Control of H.264/AVC Based on Mode-Conditional Cost Probability Distributions

A computational complexity control algorithm is proposed for an H.264 encoder running on a processor/power constrained platform. This new computational complexity control algorithm is based on a macroblock mode prediction algorithm that employs a Bayesian framework for accurate early skip decision. Complexity control is achieved by relaxing the Bayesian maximum-likelihood (ML) criterion in order to match the mode decision threshold to a target complexity level. A feedback algorithm is used to maintain the performance of the algorithm with respect to achieving an average target complexity level, reducing frame by frame complexity variance and optimizing rate-distortion performance. Experimental results show that this algorithm can effectively control the encoding computational complexity while maintaining a good rate-distortion performance at a range of target complexity levels.

Modeling of operational distortion-rate characteristics for joint source-channel coding of video

We present a method for modeling the distortion-rate characteristics of compressed video sequences. It is assumed that the source coders rely on motion-compensated prediction, and thus error propagation will contribute significantly to the degradation of the reconstructed video. It is shown that through the use of the modeled characteristics source and channel coding rate can be allocated across frames in a video sequence in order to minimize the effects of error propagation.

Combined source-channel coding for transmission of H.263 coded video with trellis-coded modulation over a slow-fading Rician channel

In this work we consider the problem of combined source-channel coding for H.263 coded video transmitted over a wireless channel modeled as a slow-fading Rician channel. We use non-binary bandwidth-efficient trellis-coded modulation (TCM) employing appropriate phase-shift keyed modulation, and determine the optimal tradeoff between source and channel coding for the Rician channel as a function of the specular-to-diffuse energy ratio and the channel SNR. We show that if feedback on channel parameters is available, the video information can be optimally coded according to channel characteristics.