Current Issue : July - September Volume : 2017 Issue Number : 3 Articles : 5 Articles
The emergence of Interactive Digital Television (iDTV) opened a set of technological possibilities that go beyond those offered\nby conventional TV. Among these opportunities we can highlight interactive contents that run together with linear TV program\n(television service where the viewer has to watch a scheduled TV program at the particular time it is offered and on the particular\nchannel it is presented on).However, developing interactive contents for this new platformis not as straightforward as, for example,\ndeveloping Internet applications. One of the options to make this development process easier and safer is to use an iDTV simulator.\nHowever, after having investigated some of the existing iDTVsimulation environments,we have found a limitation: these simulators\nmainly present solutions focused on the TV receiver, whose interactive content must be loaded in advance by the programmer\nto a local repository (e.g., Hard Drive, USB). Therefore, in this paper, we propose a tool, named BiS (Broadcast iDTV content\nSimulator), whichmakes possible a broader solution for the simulation of interactive contents. It allows simulating the transmission\nof interactive content along with the linear TV program (simulating the transmission of content over the air and in broadcast to\nthe receivers). To enable this, we defined a generic and easy-to-customize communication protocol that was implemented in the\ntool.The proposed environment differs from others because it allows simulating reception of both linear content and interactive\ncontent while running Java applications to allow such a content presentation....
The traditional image Compressive Sensing (CS) conducts block-wise sampling with the same sampling rate. However, some\nblocking artifacts often occur due to the varying block sparsity, leading to a low rate-distortion performance. To suppress these\nblocking artifacts, we propose to adaptively sample each block according to texture features in this paper. With the maximum\ngradient in 8-connected region of each pixel, we measure the texture variation of each pixel and then compute the texture contrast\nof each block. According to the distribution of texture contrast, we adaptively set the sampling rate of each block and finally build\nan image reconstruction model using these block texture contrasts. Experimental results show that our adaptive sampling scheme\nimproves the rate-distortion performance of image CS compared with the existing adaptive schemes and the reconstructed images\nby our method achieve better visual quality....
This paper describes a three-screen television system using a block recovery rate\n(BRR)-based unequal error protection (UEP). The proposed in-home wireless network uses scalable\nvideo coding (SVC) and UEP with forward error correction (FEC) for maximizing the quality of service\n(QoS) over error-prone wireless networks. For efficient FEC packet assignment, this paper proposes a\nsimple and efficient performance metric, a BRR which is defined as a recovery rate of temporal and\nquality layer from FEC assignment by analyzing the hierarchical prediction structure including the\ncurrent packet loss. It also explains the SVC layer switching scheme according to network conditions\nsuch as packet loss rate (PLR) and available bandwidth (ABW). In the experiments conducted, gains\nin video quality with the proposed UEP scheme vary from 1 to 3 dB in Y-peak signal-to-noise ratio\n(PSNR) with corresponding subjective video quality improvements....
The use of mixed spatial resolutions in multi-view video coding is a promising approach for coding videos efficiently at\nlow bitrates. It can achieve a perceived quality, which is close to the view with the highest quality, according to the\nsuppression theory of binocular vision. The aim of the work reported in this paper is to develop a new multi-view video\ncoding technique suitable for low bitrate applications in terms of coding efficiency, computational and memory\ncomplexity, when coding videos, which contain either a single or multiple scenes. The paper proposes a new prediction\narchitecture that addresses deficiencies of prediction architectures for multi-view video coding based on H.264/AVC. The\nprediction architectures which are used in mixed spatial-resolution multi-view video coding (MSR-MVC) are afflicted with\nsignificant computational complexity and require significant memory size, with regards to coding time and to the\nminimum number of reference frames. The architecture proposed herein is based on a set of investigations,\nwhich explore the effect of different inter-view prediction directions on the coding efficiency of multi-view video\ncoding, conduct a comparative study of different decimation and interpolation methods, in addition to analyzing\nblock matching statistics. The proposed prediction architecture has been integrated with an adaptive reference\nframe ordering algorithm, to provide an efficient coding solution for multi-view videos with hard scene changes.\nThe paper includes a comparative performance assessment of the proposed architecture against an extended\narchitecture based on the 3D digital multimedia broadcast (3D-DMB) and the Hierarchical B-Picture (HBP)\narchitecture, which are two most widely used architectures for MSR-MVC. The assessment experiments show that\nthe proposed architecture needs less bitrate by on average 13.1 Kbps, less coding time by 14% and less memory\nconsumption by 31.6%, compared to a corresponding codec, which deploys the extended 3D-DMB architecture\nwhen coding single-scene videos. Furthermore, the codec, which deploys the proposed architecture, accelerates\ncoding by on average 57% and requires 52% less memory, compared to a corresponding codec, which uses the\nHBP architecture. On the other hand, multi-view video coding which uses the proposed architecture needs more\nbitrate by on average 24.9 Kbps compared to a corresponding codec that uses the HBP architecture. For coding a\nmulti-view video which has hard scene changes, the proposed architecture yields less bitrate (by on average 28.7\nto 35.4 Kbps), and accelerates coding time (by on average 64 and 33%), compared to the HBP and extended 3DDMB\narchitectures, respectively. The proposed architecture will thus be most beneficial in low bitrate applications,\nwhich require multi-view video coding for video content depicting hard scene changes....
Multimedia services over mobile networks present several challenges, such as ensuring a reliable delivery of multimedia content,\navoiding undesired service disruptions, or reducing service latency. HTTP adaptive streaming addresses these problems for\nmultimedia unicast services, but it is not efficient from the point of view of radio resource consumption. In Long-Term Evolution\n(LTE) networks, multimedia broadcast services are provided over a common radio channel using a combination of forward error\ncorrection and unicast error recovery techniques at the application level. This paper discusses how to avoid service disruptions\nand reduce service latency for LTE multimedia broadcast services by adding dynamic adaptation capabilities to the unicast error\nrecovery process.The proposed solution provides a seamless mobile multimedia broadcasting without compromising the quality\nof the service perceived by the users....
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