REAL-TIME MULTIMEDIA TRANSMISSION AND PROCESSING

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Available Online at www.ijpret.com 249

INTERNATIONAL JOURNAL OF PURE AND

APPLIED RESEARCH IN ENGINEERING AND

TECHNOLOGY

A PATH FOR HORIZING YOUR INNOVATIVE WORK

REAL-TIME MULTIMEDIA TRANSMISSION AND PROCESSING

PRASHANT M. JAYLE, PROF. MAHIP M. BARTERE

1. Student of Master of Engineering in (CSE), Raisoni college of Engineering and Technology, Amravati, India. 2. Assistant professor Department of (CSE), Raisoni College of Engineering and Technology, Amravati, India.

Accepted Date: 05/03/2015; Published Date: 01/05/2015

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Abstract: The rapid increase in computing power and communication speed, coupled with computer storage facilities availability, has led to a new age of multimedia applications. Multimedia is practically everywhere and all around us we can feel its presence in almost all applications ranging from online video databases, IPTV, interactive multimedia and more recently in multimedia based social interaction. Key challenges to be addressed include specification of stream and resource characteristics, high demands on processing and Real-time delivery of mulReal-timedia streams, wireless communication between devices and transmission of streams, and architectures for the integration of numbers of devices from various manufactures with diverse demands and capabilities. In this paper, we are introducing where todays real-time multimedia applications are advancing. Then, we briefly introduces real-time, their classification, problems and techniques for their transmission. Then we studied the techniques used for Real-time multimedia signal processing, as a growing research field.

Keywords: Real-time Multimedia, Streaming multimedia, RTP (Real-time Transport Protocol), FPGA, MPEG-4 / AVG, LCT.

Corresponding Author: MR. PRASHANT M. JAYLE

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INTRODUCTION

In a few years of time, most home entertainment devices, such as TV sets and VCRs, will be fully digital, demanding computing methods to match strict temporal demands of audio and visual perception. Consequently, the concept of one cable - one box will be replaced with pictures and videos available where and when demanded in-home as part of ambient intelligence in the living space.

Similarly, video transmission and communication over mobile phone is already starting to become commonplace. The rapid increase in computing power and communication speed, coupled with computer storage facilities availability, has led to a new age of multimedia applications [1]. Multimedia is practically everywhere and all around us we can feel its presence in almost all applications ranging from online video databases, IPTV, interactive multimedia and more recently in multimedia based social interaction. Applications such as online gaming, video conferencing, video surveillance systems, industrial visual inspection systems, and many other embedded image and video processing applications will require very fast image and video processing capabilities due to their intrinsic real-time temporal requirements.

These new growing applications require high-quality data storage, easy access to multimedia content and reliable delivery. Moving ever closer to commercial deployment also aroused a higher awareness of security and intellectual property management issues. All the aforementioned requirements resulted in higher demands on various areas of research like signal processing, image/video processing and analysis, communication protocols, content search, watermarking, etc.

Nowadays, full HD video resolution is a reality in common smartphones, video cameras, and so on while multimedia market trends are focused on 4K ultra-high-definition resolution. Several companies have recently presented their new devices which are able to visualize 4K video content like the new organic light-emitting diode and also support 4k streaming. These devices evidence the limitations of current real-time multimedia coding and transmission techniques due to the huge volume of information to be processed under real-time constraints. Furthermore, most of these applications run on devices with constrained resources like smartphones, tablets, laptops, embedded systems, and still/video cameras, thus making more challenging the design and deployment of new multimedia coding and transmission techniques.

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Available Online at www.ijpret.com 251 Area Network (WLAN) that can be defined as a high speed Wireless Campus Network (WCN). The networks traffic flow determines the participating users work as a sender or receiver during the voice or video conversation. The Multimedia applications have to be kept the least data loss and maximum throughput over transmission signals/network. A new priority based scheduling scheme and dynamic channel allocation mechanisms are important. It is expected that the proposed mechanisms ensure the minimum requirement of the IMM applications which will deliver QoS with the least handoff delay and minimize the call dropping probabilities for multimedia applications though Wireless Networks.

The fundamental aspects related to image and video multimedia coding and transmission techniques with special emphasis on those techniques suitable for resource-constrained devices and applications with real-time temporal restrictions [3]. Three fundamental topics are: Efficient techniques for multimedia content representation and transmission as well as challenges found when transmitting multimedia content over modern networks. Second, Hardware/software acceleration techniques for multimedia coding and the Third one is, intelligent optimization techniques for transcoding.

II. Real Time Multimedia

Real-time multimedia refers to applications in which multimedia data has to be delivered and rendered in real time; Multimedia is a term that describes multiple forms of information consist of text, audio, video, graphics, animation, images, etc. Many of which are Real-time based, Multimedia data has to be presented in a continuous fashion, in accordance with their associated timestamp [8]. For example, video is typically rendered at 30 frames per second to give the viewers the illusion of smooth motion. As a result, multimedia applications typically have the real-time constraint. Hence, multimedia data has to be delivered and rendered in real time [5]. Today, with the advances of digital media and networking technologies, multimedia has become an indispensable feature on the Internet. A large number of distributed multimedia applications have been created, including Internet telephony, Internet videoconferencing, Internet collaboration that combines video, audio and whiteboard, Internet TV, on demand streaming or broadcasting, distance learning, distributed simulation, entertainment and gaming, etc.

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A. Interactive multimedia

In interactive multimedia applications, the delay constraint is very stringent in order to achieve interactivity. It includes Internet telephony, Internet video-conferencing, Internet collaboration, Internet gaming, etc. The latency of about 250 milliseconds is tolerable, this imposes an extremely challenging problem for interactive multimedia applications over the Internet that provides only the best effort service [4]. Over the years, great efforts have been made to facilitate the development of interactive multimedia applications over the Internet.

B. Streaming media

Streaming media technology enables the real time or on demand distribution of audio, video and multimedia on the Internet. Streaming media is the simultaneous transfer of digital media so that it is received as a continuous real-time stream. Streamed data is transmitted by a server application and received and rendered in real-time by client applications. There could be up to a few seconds of startup delay, i.e., the delay between when the server starts streaming the data and when the client starts the playback. Some of the popular streaming media products are Microsoft’s Windows Media Player and Packet Video’s embedded media player for wireless streaming to embedded devices such as the next generation multimedia phones.

Stream processing has emerged as an important model of computation in the context of multimedia and communication sub-systems of embedded System-on-Chip (SoC) architectures. The dataflow nature of streaming applications allows them to be most naturally expressed as a set of kernels iteratively operating on continuous streams of data. Streaming applications are mainly characterized by real-time constraints that demand high throughput and data bandwidth with limited global data reuse [6]. Conventional architectures fail to meet these demands due to their poorly matched execution models and the overheads associated with instruction and data movements. Multimedia market trends are focused on 4K ultra-high-definition resolution, which are able to visualize 4K video content and also support 4k streaming. These devices evidence the limitations of current real-time multimedia coding and transmission

A. Multimedia characteristics causing problems

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 Multimedia applications usually require much higher bandwidth than traditional textual applications. Eg.-A typical 25-second movie clip with a resolution of 320×240 could take 2.3 mega-bytes, which is equivalent to about 1000 screens of textual data.

 Most of the multimedia applications have stringent delay constraints, including real-time delivery. If the data does not arrive in time, the playing back process will stop and the delays or any kind of mis-delivery can easily be picked up by human ears and eyes.

 Usually many multimedia data stream are bursty due to the dynamics of different segments of the media. For most multimedia applications the receiver has a limited buffer, when data arrives too fast, the buffer will overflow and some data packets will be lost, resulting in poor quality. When data arrives too slowly, the buffer will underflow and the application will starve, causing the playing back process to freeze.

 Contrary to the high bandwidth, real-time and bursty natures of multimedia data, in reality, networks are typically shared by thousands and millions of users, and have limited bandwidth, unpredictable delay and availability. For example, the Internet provides only the best effort service, i.e., data packets can be lost, re-ordered, or delayed for a long time.

Therefore, advanced networking technologies have been designed specifically for the efficient delivery of multimedia data. There are many transport level protocol designed for reliable end-to-end delivery of data. The real-time multimedia signal processing with different formats helps to proper delivery of data.

B. Protocols used in transmission

Real time media delivery requires a maximum end-to-end delay to guarantee that live audio and video can be received and presented continuously.

 RTP (Real-Time Transport Protocol): It is designed to transport real time media. It is a packet format for multimedia data streams. RTP enables the end system to identify the type of data being transmitted, determine in what order the packets of data should be presented, and synchronize media streams from different sources.

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 RTSP (Real Time Streaming Protocol): It is a client-server multimedia presentation control protocol, designed to address the needs for efficient delivery of streamed multimedia over IP networks. It leverages existing web infrastructure and works well for both large audiences and single-viewer media-on-demand.

C. Multimedia development Language (SMIL)

SMIL is pronounced as ‘smile’ stands for Synchronized Multimedia Integration Language. It is a new markup language being developed by the World Wide Web Consortium (W3C) that would enable Web developers to divide multimedia content into separate files and streams. It send them to a user’s computer individually, and then have them displayed together as if they were a single multimedia stream. By using a single time line for all of the media on a page, their display can be properly time-coordinated and synchronized.

III. Techniques used in Multimedia processing

A. Linear Canonical Transformation (LCT)

Linear canonical transform uses matrix representation to twist the distribution of a signal into another shape, and it has many applications. Moreover, it can also be a tool for image processing in the spatial domain. Other image processing skill including reduce sampling rate, twisting of the image can also be implemented by LCT. In Hamiltonian mechanics, the linear canonical transformation (LCT) is a family of integral transforms that generalizes many classical transforms [7]. It has 4 parameters and 1 constraint, so it is a 3-dimensional family, and can be visualized as the action of the special linear groupSL2(R) on the time–frequency domain. The name "linear canonical transformation" is from canonical transformation, a map that preserves the simplistic structure, as SL2(R) can also be interpreted as the simplistic group Sp2, and thus LCTs are the linear maps of the time–frequency domain which preserve the simplistic form. The LCT generalizes the Fourier, fractional Fourier, Laplace and the Fresnel transforms as particular cases.

B. Field programmable gate arrays (FPGA)

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Available Online at www.ijpret.com 255 applications, high levels of performance can be achieved for many DSP applications providing considerable improvements over conventional microprocessor and dedicated to some specific processor solutions.

C. MPEG-4 AVC

MPEG-4 Part 10, Advanced Video Coding (MPEG-4 AVC) is a video compression format that is currently one of the most commonly used formats for the recording, compression, and distribution of video content. The demand for ever-increasing compression performance has urged the definition of a new part of the MPEG-4 standard, The development of AVC was performed by the Joint Video Team (JVT), consists of members of both MPEG and the ITU-T Video Coding Experts Group. MPEG-4 AVC is a block-oriented motion-compensation-based video compression standard developed by the ITU-TVideo Coding Experts Group (VCEG) together with the ISO/IEC JTC1Moving Picture Experts Group (MPEG).

MPEG-4is perhaps best known as being one of the video encoding standards for Blu-ray Discs. It is also widely used by streaming internet sources, such as videos from Vimeo, YouTube, and the iTunes Store, web software such as the Adobe Flash Player and Microsoft Silverlight, and also various HDTV broadcasts over terrestrial, cables and satellites [10].MPEG-4 is typically used for lossy compression in the strict mathematical sense, although the amount of loss may sometimes be imperceptible. It is also possible to create truly lossless encodings for real-time multimedia.

The H.264 video format has a very broad application range that covers all forms of digital compressed video from low bit-rate Internet streaming applications to HDTV broadcast and Digital Cinema applications with nearly lossless coding. With the use of H.264, bit rate savings of 50% or more are reported. AVCHD is a high-definition recording format designed by Sony and Panasonic that uses H.264. The CCTV (Closed Circuit TV) and Video Surveillance markets have included the technology in many products.

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Available Online at www.ijpret.com 256 error/loss robustness. It also support Flexible interlaced-scan video coding. All these features support Real-time multimedia transportation and signal processing.

D. Scalable Video Coding (SVC)

Scalable Video Coding (SVC) was defined as an amendment over MPEG4-AVC, providing efficient scalable representation of video by flexible multi-dimensional resolution adaptation. The interrelationship and adaptation between transmission/storage and compression technology is highly simplified by this scalable video representation, giving support to various network and terminal capabilities and also giving significantly increased error robustness by very simple stream truncation. Unlike previous solutions, SVC provides a high degree of flexibility in terms of scalability dimensions (supporting various temporal/spatial resolutions, SNR/fidelity levels and global/local ROI access), while the penalty in compression performance, as compared to single-layer coding and is almost negligible. Extensive results on subjective viewing have been presented in [12]. For the purpose of spatial scalability, the video is first down sampled to the required spatial resolution(s). Encoding as well as decoding starts at the lowest resolution, where an AVC compatible “base layer” bit stream will typically be used. Due to the nature of the information that is conveyed between the layers, it is in fact not necessary to run predictive decoder loops for the lower layers. Only information that is directly decodable, such as motion, mode, residual or intra information are conveyed to the next-higher layer. Therefore, the decoding process of SVC can be designated as single-loop decoding.

IV. CONCLUSION

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