Investigating low-bitrate, low-complexity H.264 region of interest techniques in error-prone environments

The H.264/AVC video coding standard leverages advanced compression methods to provide a significant increase in performance over previous CODECs in terms of picture quality, bitrate, and flexibility. The specification itself provides several profiles and levels that allow customization through the use of various advanced features. In addition to these features, several new video coding techniques have been developed since the standard\u27s inception. One such technique known as Region of Interest (RoI) coding has been in existence since before H.264\u27s formalization, and several means of implementing RoI coding in H.264 have been proposed. Region of Interest coding operates under the assumption that one or more regions of a sequence have higher priority than the rest of the video. One goal of RoI coding is to provide a decrease in bitrate without significant loss of perceptual quality, and this is particularly applicable to low complexity environments, if the proper implementation is used. Furthermore, RoI coding may allow for enhanced error resilience in the selected regions if desired, making RoI suitable for both low-bitrate and error-prone scenarios. The goal of this thesis project was to examine H.264 Region of Interest coding as it applies to such scenarios. A modified version of the H.264 JM Reference Software was created in which all non-Baseline profile features were removed. Six low-complexity RoI coding techniques, three targeting rate control and three targeting error resilience, were selected for implementation. Error and distortion modeling tools were created to enhance the quality of experimental data. Results were gathered by varying a range of coding parameters including frame size, target bitrate, and macroblock error rates. Methods were then examined based on their rate-distortion curves, ability to achieve target bitrates accurately, and per-region distortions where applicable

Current video compression algorithms: Comparisons, optimizations, and improvements

Compression algorithms have evolved significantly in recent years. Audio, still image, and video can be compressed significantly by taking advantage of the natural redundancies that occur within them. Video compression in particular has made significant advances. MPEG-1 and MPEG-2, two of the major video compression standards, allowed video to be compressed at very low bit rates compared to the original video. The compression ratio for video that is perceptually lossless (losses can\u27t be visually perceived) can even be as high as 40 or 50 to 1 for certain videos. Videos with a small degradation in quality can be compressed at 100 to 1 or more; Although the MPEG standards provided low bit rate compression, even higher quality compression is required for efficient transmission over limited bandwidth networks, wireless networks, and broadcast mediums. Significant gains have been made over the current MPEG-2 standard in a newly developed standard called the Advanced Video Coder, also known as H.264 and MPEG-4 part 10. (Abstract shortened by UMI.)

Mode decision for the H.264/AVC video coding standard

H.264/AVC video coding standard gives us a very promising future for the field of video broadcasting and communication because of its high coding efficiency compared with other older video coding standards. However, high coding efficiency also carries high computational complexity. Fast motion estimation and fast mode decision are two very useful techniques which can significantly reduce computational complexity. This thesis focuses on the field of fast mode decision. The goal of this thesis is that for very similar RD performance compared with H.264/AVC video coding standard, we aim to find new fast mode decision techniques which can afford significant time savings. [Continues.

QoE for Mobile Streaming

No abstract

Slice-Level Trading of Quality and Performance in Decoding H.264 Video: Slice-basiertes Abwägen zwischen Qualität und Leistung beim Dekodieren von H.264-Video

When a demanding video decoding task requires more CPU resources then available, playback degrades ungracefully today: The decoder skips frames selected arbitrarily or by simple heuristics, which is noticed by the viewer as jerky motion in the good case or as images completely breaking up in the bad case. The latter can happen due to missing reference frames. This thesis provides a way to schedule individual decoding tasks based on a cost for performance trade. Therefore, I will present a way to preprocess a video, generating estimates for the cost in terms of execution time and the performance in terms of perceived visual quality. The granularity of the scheduling decision is a single slice, which leads to a much more fine-grained approach than dealing with entire frames. Together with an actual scheduler implementation that uses the generated estimates, this work allows for higher perceived quality video playback in case of CPU overload.Wenn eine anspruchsvolle Video-Dekodierung mehr Prozessor-Ressourcen benötigt, als verfügbar sind, dann verschlechtert sich die Abspielqualität mit aktuellen Methoden drastisch: Willkürlich oder mit einfachen Heuristiken ausgewählten Bilder werden nicht dekodiert. Diese Auslassung nimmt der Betrachter im günstigsten Fall nur als ruckelnde Bewegung wahr, im ungünstigen Fall jedoch als komplettes Zusammenbrechen nachfolgender Bilder durch Folgefehler im Dekodierprozess. Meine Arbeit ermöglicht es, einzelne Teilaufgaben des Dekodierprozesses anhand einer Kosten-Nutzen-Analyse einzuplanen. Dafür ermittle ich die Kosten im Sinne von Rechenzeitbedarf und den Nutzen im Sinne von visueller Qualität für einzelne Slices eines H.264 Videos. Zusammen mit einer Implementierung eines Schedulers, der diese Werte nutzt, erlaubt meine Arbeit höhere vom Betrachter wahrgenommene Videoqualität bei knapper Prozessorzeit

Error resilient packet switched H.264 video telephony over third generation networks.

Real-time video communication over wireless networks is a challenging problem because wireless channels suffer from fading, additive noise and interference, which translate into packet loss and delay. Since modern video encoders deliver video packets with decoding dependencies, packet loss and delay can significantly degrade the video quality at the receiver. Many error resilience mechanisms have been proposed to combat packet loss in wireless networks, but only a few were specifically designed for packet switched video telephony over Third Generation (3G) networks. The first part of the thesis presents an error resilience technique for packet switched video telephony that combines application layer Forward Error Correction (FEC) with rateless codes, Reference Picture Selection (RPS) and cross layer optimization. Rateless codes have lower encoding and decoding computational complexity compared to traditional error correcting codes. One can use them on complexity constrained hand-held devices. Also, their redundancy does not need to be fixed in advance and any number of encoded symbols can be generated on the fly. Reference picture selection is used to limit the effect of spatio-temporal error propagation. Limiting the effect of spatio-temporal error propagation results in better video quality. Cross layer optimization is used to minimize the data loss at the application layer when data is lost at the data link layer. Experimental results on a High Speed Packet Access (HSPA) network simulator for H.264 compressed standard video sequences show that the proposed technique achieves significant Peak Signal to Noise Ratio (PSNR) and Percentage Degraded Video Duration (PDVD) improvements over a state of the art error resilience technique known as Interactive Error Control (IEC), which is a combination of Error Tracking and feedback based Reference Picture Selection. The improvement is obtained at a cost of higher end-to-end delay. The proposed technique is improved by making the FEC (Rateless code) redundancy channel adaptive. Automatic Repeat Request (ARQ) is used to adjust the redundancy of the Rateless codes according to the channel conditions. Experimental results show that the channel adaptive scheme achieves significant PSNR and PDVD improvements over the static scheme for a simulated Long Term Evolution (LTE) network. In the third part of the thesis, the performance of the previous two schemes is improved by making the transmitter predict when rateless decoding will fail. In this case, reference picture selection is invoked early and transmission of encoded symbols for that source block is aborted. Simulations for an LTE network show that this results in video quality improvement and bandwidth savings. In the last part of the thesis, the performance of the adaptive technique is improved by exploiting the history of the wireless channel. In a Rayleigh fading wireless channel, the RLC-PDU losses are correlated under certain conditions. This correlation is exploited to adjust the redundancy of the Rateless code and results in higher Rateless code decoding success rate and higher video quality. Simulations for an LTE network show that the improvement was significant when the packet loss rate in the two wireless links was 10%. To facilitate the implementation of the proposed error resilience techniques in practical scenarios, RTP/UDP/IP level packetization schemes are also proposed for each error resilience technique. Compared to existing work, the proposed error resilience techniques provide better video quality. Also, more emphasis is given to implementation issues in 3G networks

Adaptive intra refresh for robust wireless multi-view video

This thesis was submitted for the award of PhD and was awarded by Brunel University LondonMobile wireless communication technology is a fast developing field and every day new mobile communication techniques and means are becoming available. In this thesis multi-view video (MVV) is also refers to as 3D video. Thus, the 3D video signals through wireless communication are shaping telecommunication industry and academia. However, wireless channels are prone to high level of bit and burst errors that largely deteriorate the quality of service (QoS). Noise along the wireless transmission path can introduce distortion or make a compressed bitstream lose vital information. The error caused by noise progressively spread to subsequent frames and among multiple views due to prediction. This error may compel the receiver to pause momentarily and wait for the subsequent INTRA picture to continue decoding. The pausing of video stream affects the user's Quality of Experience (QoE). Thus, an error resilience strategy is needed to protect the compressed bitstream against transmission errors. This thesis focuses on error resilience Adaptive Intra Refresh (AIR) technique. The AIR method is developed to make the compressed 3D video more robust to channel errors. The process involves periodic injection of Intra-coded macroblocks in a cyclic pattern using H.264/AVC standard. The algorithm takes into account individual features in each macroblock and the feedback information sent by the decoder about the channel condition in order to generate an MVV-AIR map. MVV-AIR map generation regulates the order of packets arrival and identifies the motion activities in each macroblock. Based on the level of motion activity contained in each macroblock, the MVV-AIR map classifies frames as high or low motion macroblocks. A proxy MVV-AIR transcoder is used to validate the efficiency of the generated MVV-AIR map. The MVV-AIR transcoding algorithm uses spatial and views downscaling scheme to convert from MVV to single view. Various experimental results indicate that the proposed error resilient MVV-AIR transcoder technique effectively improves the quality of reconstructed 3D video in wireless networks. A comparison of MVV-AIR transcoder algorithm with some traditional error resilience techniques demonstrates that MVV-AIR algorithm performs better in an error prone channel. Results of simulation revealed significant improvements in both objective and subjective qualities. No additional computational complexity emanates from the scheme while the QoS and QoE requirements are still fully met.Tertiary Institution Trust Fund (TETFund) of Nigeri

Error resilience and concealment techniques for high-efficiency video coding

This thesis investigates the problem of robust coding and error concealment in High Efficiency Video Coding (HEVC). After a review of the current state of the art, a simulation study about error robustness, revealed that the HEVC has weak protection against network losses with significant impact on video quality degradation. Based on this evidence, the first contribution of this work is a new method to reduce the temporal dependencies between motion vectors, by improving the decoded video quality without compromising the compression efficiency. The second contribution of this thesis is a two-stage approach for reducing the mismatch of temporal predictions in case of video streams received with errors or lost data. At the encoding stage, the reference pictures are dynamically distributed based on a constrained Lagrangian rate-distortion optimization to reduce the number of predictions from a single reference. At the streaming stage, a prioritization algorithm, based on spatial dependencies, selects a reduced set of motion vectors to be transmitted, as side information, to reduce mismatched motion predictions at the decoder. The problem of error concealment-aware video coding is also investigated to enhance the overall error robustness. A new approach based on scalable coding and optimally error concealment selection is proposed, where the optimal error concealment modes are found by simulating transmission losses, followed by a saliency-weighted optimisation. Moreover, recovery residual information is encoded using a rate-controlled enhancement layer. Both are transmitted to the decoder to be used in case of data loss. Finally, an adaptive error resilience scheme is proposed to dynamically predict the video stream that achieves the highest decoded quality for a particular loss case. A neural network selects among the various video streams, encoded with different levels of compression efficiency and error protection, based on information from the video signal, the coded stream and the transmission network. Overall, the new robust video coding methods investigated in this thesis yield consistent quality gains in comparison with other existing methods and also the ones implemented in the HEVC reference software. Furthermore, the trade-off between coding efficiency and error robustness is also better in the proposed methods