Yonghee Lee

Reducing IPTV Chan nel Switching Time using H.264 Scalable Video Coding

In this paper, we aim to reduce the channel switching time for Internet protocol TV (IPTV) without unduly influencing the picture quality. For this purpose, we propose to adopt the H.264 scalable video coding scheme, for which we allocate a base layer and enhancement layers of each channel to two separate multicast groups. In preview mode, users access the base layers of different channels already stored in a buffer, so they can switch between channels without delay. In watching mode, they use both the base and enhancement layers of the selected channel to achieve full quality. While providing fast channel switching in the preview mode, our approach proves to maintain the picture quality similar to the case of single layer coding. An experimental result, for example, shows that, even with complicated scenes, a 1.5 Mbps scalable video stream for IPTV has achieved a good picture quality with a PSNR of 33.7 dB1.

Design of a mobile video streaming system using adaptive spatial resolution control

An efficient mobile video streaming system needs to cope with unstable network bandwidth and limited battery life. We propose a novel streaming system which jointly considers picture quality, bit-rate and energy consumption. Reducing the spatial resolution of a video stream adaptively proves to be more efficient in terms of picture quality and energy consumption than conventional rate control using only adjustment of quantization parameter. We apply the same scheme to scalable coding for large-scale mobile video streaming. This extends the adaptation of an SVC stream to lower bit-rates, while maintaining temporal stability. Our approach has been shown to improve picture quality by approximately 0.5 dB in low bit-rate conditions, and also reduces energy consumption by more than 50% compared to conventional video streaming.

Quality-adaptive requantization for low-energy MPEG-4 video decoding in mobile devices

Current mobile devices usually provide streaming media for users. While the online multimedia processing requires intensive computation, the characteristics of mobility and portability place a severe energy constraint on the system. In this paper, we aim to develop a systematic methodology for dealing with low-energy computation for the MPEG-4 video decoding. Our approach is based on a new fine-controllable, quality-adaptive technique to reduce data volumes, which results in energy saving. To do so, we introduce a requantization step to the video decoding process. The proposed requantization ensures that the energy consumption reduces at higher rate than the video quality degrades, and that the videos remain intelligible to a human viewer. The experimental results show that the energy consumption is reduced by up to 42% with 13% quality degradation, thereby confirming the efficacy of the quality-adaptive requantization.

Determining efficient bit stream extraction paths in H.264/AVC scalable video coding

The scalable video coding (SVC) amendment of H.264/AVC offers three scalability dimensions: spatial, temporal, and quality scalabilities. Since these three dimensions can be easily combined, a single SVC bit stream has various extraction points, providing many sub-streams. When a specific bit rate is given, finding an optimal extraction point among various extraction points is a difficult problem due to the difference in the metric of each scalability dimension. We develop a method to efficiently transform three scalability dimensions into utility functions and propose an algorithm to find an efficient extraction path by using the points of inflection. Experimental results show that our approach can find a better extraction path as compared to the Joint Scalable Video Model (JSVM) basic extractor. Moreover, using the determined extraction path for an SVC bit stream is less complex owing to its monotonically increasing property.

Adaptive Spatial Resolution Control Scheme for Mobile Video Applications

Video streams can be compressed to fit the available network by controlling three factors; temporal resolution, spatial resolution and picture quality. Controlling picture quality by modifying the quantization parameter (QP) is most widely used. But we demonstrate that reducing the spatial resolution is more effective in a low bit-rate environment, and we show how to find the optimal spatial resolution for the available bandwidth. Varying the spatial resolution is especially effective 1) when the bandwidth between the video encoder and the displaying device varies considerably with time, which is the case in wireless networks, and 2) when the display device is sensitive to energy saving. Both of these considerations are met by a portable media player which is displaying streaming video content transmitted by a remote video server through a wireless network. If the bit-rate is low, our technique can improve the picture quality by more than 1 db compared to adjustment of QP, accompanied by a halving of energy consumption.

An experimental analysis of the effect of the operating system on memory performance in embedded multimedia computing

As embedded systems grow in size and complexity, an operating system has become essential to simplify the design of system software, for which more accurate analysis of its impact on memory performance is required. In this paper, we intend to investigate how the OS influences memory performance at run time by quantitatively evaluating the memory system behavior of an MPEG-4 application running on embedded Linux. Through the use of extensive simulations we have confirmed that the OS has poor memory performance with less memory locality than applications. The results of our experimental analysis are deemed useful for helping embedded system designers understand the memory performance of the OS and the application within a system, extending their capability to design a more power-aware and faster system.

Luminance scalable coding using H.264/AVC SVC extensions for mobile video applications

We propose a luminance scalable video coding scheme (LSC) that uses the scalable video coding (SVC) extension of H.264/AVC to reduce the power consumption of mobile devices. The insufficient battery life of mobile hand-held devices is the main obstacle for mobile video applications. In particular, liquid crystal displays consume a large portion of the system power. Building on previous power reduction schemes, such as dynamic backlight luminance scaling, we exploit SVC which is used to adapt a video stream to the preferences of users, different mobile capabilities, and varying network conditions. Our video coding scheme can reduce the power consumed by an LCD display by more than 20%, even though it has a lower overhead than previous schemes and does not require any modification of the decoders.

Low-complexity aggregation of collected images with correlated fields of view in wireless video sensor networks

Wireless video sensor networks (WVSNs) require video data from sensor nodes to be delivered efficiently. Cameras in adjacent video nodes tend to have correlated fields of view (FoVs) or overlapping part when a sufficient number of video sensors are deployed. This paper proposes a data aggregation technique for WVSNs to remove the spatial redundancy, thereby reducing energy consumption and response time. Our approach exploits the correlation between discrete cosine transform (DCT) coefficients pairs of two intra-coded images from cameras with overlapping FoVs. Experiments show that an intermediate node en route to the base station achieves bit-rate savings up to 18.9%. This scheme is less complicated than other video and image coding techniques that exploit correlated FoV, allowing resource-constrained video sensors to operate more reliably and longer.

Errata to "Design of a Mobile Video Streaming System using Adaptive Spatial Resolution Control" [Aug 09 1682-1689]

In the above titled paper (ibid., vol. 55, no. 3, pp. 1682-1689, Aug. 09), Figures 3 and 11 were inadvertently omitted in production. The figures are presented here.

Experimental Performance Evaluation of Embedded Linux Using Alternative CPU Core Organizations

An operating system has become essential to simplify the design of software for embedded systems, and this in turn requires accurate analyses of OS performance to help with more power-aware and efficient computing. For this purpose, we attempt to evaluate the major Linux subsystems: process management, memory management, inter-process communication (IPC), and networking, while changing the organization of the core components of the CPU such as cache size, clock frequency, memory management unit (MMU), and floating-point unit (FPU). We run a set of benchmark applications which separately assess the OS services provided by each subsystem. The experimental results are then analyzed as regards the CPU design parameters. As a consequence, we observe that changes in the design parameters exert a varying degree of influence over the system performance depending on OS services: In the best case, performance improvement reaches 100% while ranging from 34% to 36% on average.