506 research outputs found

    Advanced solutions for quality-oriented multimedia broadcasting

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    Multimedia content is increasingly being delivered via different types of networks to viewers in a variety of locations and contexts using a variety of devices. The ubiquitous nature of multimedia services comes at a cost, however. The successful delivery of multimedia services will require overcoming numerous technological challenges many of which have a direct effect on the quality of the multimedia experience. For example, due to dynamically changing requirements and networking conditions, the delivery of multimedia content has traditionally adopted a best effort approach. However, this approach has often led to the end-user perceived quality of multimedia-based services being negatively affected. Yet the quality of multimedia content is a vital issue for the continued acceptance and proliferation of these services. Indeed, end-users are becoming increasingly quality-aware in their expectations of multimedia experience and demand an ever-widening spectrum of rich multimedia-based services. As a consequence, there is a continuous and extensive research effort, by both industry and academia, to find solutions for improving the quality of multimedia content delivered to the users; as well, international standards bodies, such as the International Telecommunication Union (ITU), are renewing their effort on the standardization of multimedia technologies. There are very different directions in which research has attempted to find solutions in order to improve the quality of the rich media content delivered over various network types. It is in this context that this special issue on broadcast multimedia quality of the IEEE Transactions on Broadcasting illustrates some of these avenues and presents some of the most significant research results obtained by various teams of researchers from many countries. This special issue provides an example, albeit inevitably limited, of the richness and breath of the current research on multimedia broadcasting services. The research i- - ssues addressed in this special issue include, among others, factors that influence user perceived quality, encoding-related quality assessment and control, transmission and coverage-based solutions and objective quality measurements

    Audio Coding Based on Integer Transforms

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    Die Audiocodierung hat sich in den letzten Jahren zu einem sehr populĂ€ren Forschungs- und Anwendungsgebiet entwickelt. Insbesondere gehörangepasste Verfahren zur Audiocodierung, wie etwa MPEG-1 Layer-3 (MP3) oder MPEG-2 Advanced Audio Coding (AAC), werden hĂ€ufig zur effizienten Speicherung und Übertragung von Audiosignalen verwendet. FĂŒr professionelle Anwendungen, wie etwa die Archivierung und Übertragung im Studiobereich, ist hingegen eher eine verlustlose Audiocodierung angebracht. Die bisherigen AnsĂ€tze fĂŒr gehörangepasste und verlustlose Audiocodierung sind technisch völlig verschieden. Moderne gehörangepasste Audiocoder basieren meist auf FilterbĂ€nken, wie etwa der ĂŒberlappenden orthogonalen Transformation "Modifizierte Diskrete Cosinus-Transformation" (MDCT). Verlustlose Audiocoder hingegen verwenden meist prĂ€diktive Codierung zur Redundanzreduktion. Nur wenige AnsĂ€tze zur transformationsbasierten verlustlosen Audiocodierung wurden bisher versucht. Diese Arbeit prĂ€sentiert einen neuen Ansatz hierzu, der das Lifting-Schema auf die in der gehörangepassten Audiocodierung verwendeten ĂŒberlappenden Transformationen anwendet. Dies ermöglicht eine invertierbare Integer-Approximation der ursprĂŒnglichen Transformation, z.B. die IntMDCT als Integer-Approximation der MDCT. Die selbe Technik kann auch fĂŒr FilterbĂ€nke mit niedriger Systemverzögerung angewandt werden. Weiterhin ermöglichen ein neuer, mehrdimensionaler Lifting-Ansatz und eine Technik zur Spektralformung von Quantisierungsfehlern eine Verbesserung der Approximation der ursprĂŒnglichen Transformation. Basierend auf diesen neuen Integer-Transformationen werden in dieser Arbeit neue Verfahren zur Audiocodierung vorgestellt. Die Verfahren umfassen verlustlose Audiocodierung, eine skalierbare verlustlose Erweiterung eines gehörangepassten Audiocoders und einen integrierten Ansatz zur fein skalierbaren gehörangepassten und verlustlosen Audiocodierung. Schließlich wird mit Hilfe der Integer-Transformationen ein neuer Ansatz zur unhörbaren Einbettung von Daten mit hohen Datenraten in unkomprimierte Audiosignale vorgestellt.In recent years audio coding has become a very popular field for research and applications. Especially perceptual audio coding schemes, such as MPEG-1 Layer-3 (MP3) and MPEG-2 Advanced Audio Coding (AAC), are widely used for efficient storage and transmission of music signals. Nevertheless, for professional applications, such as archiving and transmission in studio environments, lossless audio coding schemes are considered more appropriate. Traditionally, the technical approaches used in perceptual and lossless audio coding have been separate worlds. In perceptual audio coding, the use of filter banks, such as the lapped orthogonal transform "Modified Discrete Cosine Transform" (MDCT), has been the approach of choice being used by many state of the art coding schemes. On the other hand, lossless audio coding schemes mostly employ predictive coding of waveforms to remove redundancy. Only few attempts have been made so far to use transform coding for the purpose of lossless audio coding. This work presents a new approach of applying the lifting scheme to lapped transforms used in perceptual audio coding. This allows for an invertible integer-to-integer approximation of the original transform, e.g. the IntMDCT as an integer approximation of the MDCT. The same technique can also be applied to low-delay filter banks. A generalized, multi-dimensional lifting approach and a noise-shaping technique are introduced, allowing to further optimize the accuracy of the approximation to the original transform. Based on these new integer transforms, this work presents new audio coding schemes and applications. The audio coding applications cover lossless audio coding, scalable lossless enhancement of a perceptual audio coder and fine-grain scalable perceptual and lossless audio coding. Finally an approach to data hiding with high data rates in uncompressed audio signals based on integer transforms is described

    Audio Coding Based on Integer Transforms

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    Die Audiocodierung hat sich in den letzten Jahren zu einem sehr populĂ€ren Forschungs- und Anwendungsgebiet entwickelt. Insbesondere gehörangepasste Verfahren zur Audiocodierung, wie etwa MPEG-1 Layer-3 (MP3) oder MPEG-2 Advanced Audio Coding (AAC), werden hĂ€ufig zur effizienten Speicherung und Übertragung von Audiosignalen verwendet. FĂŒr professionelle Anwendungen, wie etwa die Archivierung und Übertragung im Studiobereich, ist hingegen eher eine verlustlose Audiocodierung angebracht. Die bisherigen AnsĂ€tze fĂŒr gehörangepasste und verlustlose Audiocodierung sind technisch völlig verschieden. Moderne gehörangepasste Audiocoder basieren meist auf FilterbĂ€nken, wie etwa der ĂŒberlappenden orthogonalen Transformation "Modifizierte Diskrete Cosinus-Transformation" (MDCT). Verlustlose Audiocoder hingegen verwenden meist prĂ€diktive Codierung zur Redundanzreduktion. Nur wenige AnsĂ€tze zur transformationsbasierten verlustlosen Audiocodierung wurden bisher versucht. Diese Arbeit prĂ€sentiert einen neuen Ansatz hierzu, der das Lifting-Schema auf die in der gehörangepassten Audiocodierung verwendeten ĂŒberlappenden Transformationen anwendet. Dies ermöglicht eine invertierbare Integer-Approximation der ursprĂŒnglichen Transformation, z.B. die IntMDCT als Integer-Approximation der MDCT. Die selbe Technik kann auch fĂŒr FilterbĂ€nke mit niedriger Systemverzögerung angewandt werden. Weiterhin ermöglichen ein neuer, mehrdimensionaler Lifting-Ansatz und eine Technik zur Spektralformung von Quantisierungsfehlern eine Verbesserung der Approximation der ursprĂŒnglichen Transformation. Basierend auf diesen neuen Integer-Transformationen werden in dieser Arbeit neue Verfahren zur Audiocodierung vorgestellt. Die Verfahren umfassen verlustlose Audiocodierung, eine skalierbare verlustlose Erweiterung eines gehörangepassten Audiocoders und einen integrierten Ansatz zur fein skalierbaren gehörangepassten und verlustlosen Audiocodierung. Schließlich wird mit Hilfe der Integer-Transformationen ein neuer Ansatz zur unhörbaren Einbettung von Daten mit hohen Datenraten in unkomprimierte Audiosignale vorgestellt.In recent years audio coding has become a very popular field for research and applications. Especially perceptual audio coding schemes, such as MPEG-1 Layer-3 (MP3) and MPEG-2 Advanced Audio Coding (AAC), are widely used for efficient storage and transmission of music signals. Nevertheless, for professional applications, such as archiving and transmission in studio environments, lossless audio coding schemes are considered more appropriate. Traditionally, the technical approaches used in perceptual and lossless audio coding have been separate worlds. In perceptual audio coding, the use of filter banks, such as the lapped orthogonal transform "Modified Discrete Cosine Transform" (MDCT), has been the approach of choice being used by many state of the art coding schemes. On the other hand, lossless audio coding schemes mostly employ predictive coding of waveforms to remove redundancy. Only few attempts have been made so far to use transform coding for the purpose of lossless audio coding. This work presents a new approach of applying the lifting scheme to lapped transforms used in perceptual audio coding. This allows for an invertible integer-to-integer approximation of the original transform, e.g. the IntMDCT as an integer approximation of the MDCT. The same technique can also be applied to low-delay filter banks. A generalized, multi-dimensional lifting approach and a noise-shaping technique are introduced, allowing to further optimize the accuracy of the approximation to the original transform. Based on these new integer transforms, this work presents new audio coding schemes and applications. The audio coding applications cover lossless audio coding, scalable lossless enhancement of a perceptual audio coder and fine-grain scalable perceptual and lossless audio coding. Finally an approach to data hiding with high data rates in uncompressed audio signals based on integer transforms is described

    Reviews on Technology and Standard of Spatial Audio Coding

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    Market  demands  on a more impressive entertainment media have motivated for delivery of three dimensional  (3D) audio content to  home consumers  through Ultra  High  Definition  TV  (UHDTV), the next generation of TV broadcasting, where spatial  audio  coding plays  fundamental role. This paper reviews fundamental concept on spatial audio coding which includes technology, standard, and application. Basic principle of object-based audio reproduction system  will also be elaborated, compared  to  the  traditional channel-based system, to provide good understanding on this popular interactive audio reproduction system which gives end users flexibility to render  their  own preferred  audio composition.Keywords : spatial audio, audio coding, multi-channel audio signals, MPEG standard, object-based audi

    Audio Compression using a Modified Vector Quantization algorithm for Mastering Applications

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    Audio data compression is used to reduce the transmission bandwidth and storage requirements of audio data. It is the second stage in the audio mastering process with audio equalization being the first stage. Compression algorithms such as BSAC, MP3 and AAC are used as standards in this paper. The challenge faced in audio compression is compressing the signal at low bit rates. The previous algorithms which work well at low bit rates cannot be dominant at higher bit rates and vice-versa. This paper proposes an altered form of vector quantization algorithm which produces a scalable bit stream which has a number of fine layers of audio fidelity. This modified form of the vector quantization algorithm is used to generate a perceptually audio coder which is scalable and uses the quantization and encoding stages which are responsible for the psychoacoustic and arithmetical terminations that are actually detached as practically all the data detached during the prediction phases at the encoder side is supplemented towards the audio signal at decoder stage. Therefore, clearly the quantization phase which is modified to produce a bit stream which is scalable. This modified algorithm works well at both lower and higher bit rates. Subjective evaluations were done by audio professionals using the MUSHRA test and the mean normalized scores at various bit rates was noted and compared with the previous algorithms

    Scalable and perceptual audio compression

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    This thesis deals with scalable perceptual audio compression. Two scalable perceptual solutions as well as a scalable to lossless solution are proposed and investigated. One of the scalable perceptual solutions is built around sinusoidal modelling of the audio signal whilst the other is built on a transform coding paradigm. The scalable coders are shown to scale both in a waveform matching manner as well as a psychoacoustic manner. In order to measure the psychoacoustic scalability of the systems investigated in this thesis, the similarity between the original signal\u27s psychoacoustic parameters and that of the synthesized signal are compared. The psychoacoustic parameters used are loudness, sharpness, tonahty and roughness. This analysis technique is a novel method used in this thesis and it allows an insight into the perceptual distortion that has been introduced by any coder analyzed in this manner

    Performance Evaluation of Audio Coding by Amalgam AAC and FLAC Audio codec using MDCT and INTMDCT Algorithm

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    The MDCT and IntMDCT Algorithm is widely utilized is Audio coding.By lifting scheme or rounding operation IntegerMDCT is evolved from Modified Discrete Cosine Transform.This method acquire the properties of  MDCT and  contribute excelling invertiblity and good spectral mean.In this paper we discuss about the audio codec like AAC and FLAC using MDCT and Integer MDCT algorithm and to find which algorithm shows better Compression Ratio(CR).The confines of this task is to hybriding lossy and lossless audio codec with  diminished bit rate but with finer sound quality. Certainly the quality of the audio is figure out by Subjective and Objective testing which is in terms of MOS (Mean opinion square) , ABx and some of the hearing aid testing methodology like PEAQ(Perceptual  Evaluation Audio Quality)  and ODG(Objective Difference Grade)is followed. Execution measure, that is Compression Ratio(CR) and Sound Pressure Level (SPL) is approximated

    Providing 3D video services: the challenge from 2D to 3DTV quality of experience

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    Recently, three-dimensional (3D) video has decisively burst onto the entertainment industry scene, and has arrived in households even before the standardization process has been completed. 3D television (3DTV) adoption and deployment can be seen as a major leap in television history, similar to previous transitions from black and white (B&W) to color, from analog to digital television (TV), and from standard definition to high definition. In this paper, we analyze current 3D video technology trends in order to define a taxonomy of the availability and possible introduction of 3D-based services. We also propose an audiovisual network services architecture which provides a smooth transition from two-dimensional (2D) to 3DTV in an Internet Protocol (IP)-based scenario. Based on subjective assessment tests, we also analyze those factors which will influence the quality of experience in those 3D video services, focusing on effects of both coding and transmission errors. In addition, examples of the application of the architecture and results of assessment tests are provided
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