Data compression techniques applied to high resolution high frame rate video technology

An investigation is presented of video data compression applied to microgravity space experiments using High Resolution High Frame Rate Video Technology (HHVT). An extensive survey of methods of video data compression, described in the open literature, was conducted. The survey examines compression methods employing digital computing. The results of the survey are presented. They include a description of each method and assessment of image degradation and video data parameters. An assessment is made of present and near term future technology for implementation of video data compression in high speed imaging system. Results of the assessment are discussed and summarized. The results of a study of a baseline HHVT video system, and approaches for implementation of video data compression, are presented. Case studies of three microgravity experiments are presented and specific compression techniques and implementations are recommended

Implementation issues in source coding

An edge preserving image coding scheme which can be operated in both a lossy and a lossless manner was developed. The technique is an extension of the lossless encoding algorithm developed for the Mars observer spectral data. It can also be viewed as a modification of the DPCM algorithm. A packet video simulator was also developed from an existing modified packet network simulator. The coding scheme for this system is a modification of the mixture block coding (MBC) scheme described in the last report. Coding algorithms for packet video were also investigated

Audio Coding Based on Integer Transforms

Die Audiocodierung hat sich in den letzten Jahren zu einem sehr populären Forschungs- und Anwendungsgebiet entwickelt. Insbesondere gehörangepasste Verfahren zur Audiocodierung, wie etwa MPEG-1 Layer-3 (MP3) oder MPEG-2 Advanced Audio Coding (AAC), werden häufig zur effizienten Speicherung und Übertragung von Audiosignalen verwendet. Für professionelle Anwendungen, wie etwa die Archivierung und Übertragung im Studiobereich, ist hingegen eher eine verlustlose Audiocodierung angebracht. Die bisherigen Ansätze für gehörangepasste und verlustlose Audiocodierung sind technisch völlig verschieden. Moderne gehörangepasste Audiocoder basieren meist auf Filterbänken, wie etwa der überlappenden orthogonalen Transformation "Modifizierte Diskrete Cosinus-Transformation" (MDCT). Verlustlose Audiocoder hingegen verwenden meist prädiktive Codierung zur Redundanzreduktion. Nur wenige Ansätze zur transformationsbasierten verlustlosen Audiocodierung wurden bisher versucht. Diese Arbeit präsentiert einen neuen Ansatz hierzu, der das Lifting-Schema auf die in der gehörangepassten Audiocodierung verwendeten überlappenden Transformationen anwendet. Dies ermöglicht eine invertierbare Integer-Approximation der ursprünglichen Transformation, z.B. die IntMDCT als Integer-Approximation der MDCT. Die selbe Technik kann auch für Filterbänke mit niedriger Systemverzögerung angewandt werden. Weiterhin ermöglichen ein neuer, mehrdimensionaler Lifting-Ansatz und eine Technik zur Spektralformung von Quantisierungsfehlern eine Verbesserung der Approximation der ursprünglichen 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

Die Audiocodierung hat sich in den letzten Jahren zu einem sehr populären Forschungs- und Anwendungsgebiet entwickelt. Insbesondere gehörangepasste Verfahren zur Audiocodierung, wie etwa MPEG-1 Layer-3 (MP3) oder MPEG-2 Advanced Audio Coding (AAC), werden häufig zur effizienten Speicherung und Übertragung von Audiosignalen verwendet. Für professionelle Anwendungen, wie etwa die Archivierung und Übertragung im Studiobereich, ist hingegen eher eine verlustlose Audiocodierung angebracht. Die bisherigen Ansätze für gehörangepasste und verlustlose Audiocodierung sind technisch völlig verschieden. Moderne gehörangepasste Audiocoder basieren meist auf Filterbänken, wie etwa der überlappenden orthogonalen Transformation "Modifizierte Diskrete Cosinus-Transformation" (MDCT). Verlustlose Audiocoder hingegen verwenden meist prädiktive Codierung zur Redundanzreduktion. Nur wenige Ansätze zur transformationsbasierten verlustlosen Audiocodierung wurden bisher versucht. Diese Arbeit präsentiert einen neuen Ansatz hierzu, der das Lifting-Schema auf die in der gehörangepassten Audiocodierung verwendeten überlappenden Transformationen anwendet. Dies ermöglicht eine invertierbare Integer-Approximation der ursprünglichen Transformation, z.B. die IntMDCT als Integer-Approximation der MDCT. Die selbe Technik kann auch für Filterbänke mit niedriger Systemverzögerung angewandt werden. Weiterhin ermöglichen ein neuer, mehrdimensionaler Lifting-Ansatz und eine Technik zur Spektralformung von Quantisierungsfehlern eine Verbesserung der Approximation der ursprünglichen 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

A Cost Shared Quantization Algorithm and its Implementation for Multi-Standard Video CODECS

The current trend of digital convergence creates the need for the video encoder and decoder system, known as codec in short, that should support multiple video standards on a single platform. In a modern video codec, quantization is a key unit used for video compression. In this thesis, a generalized quantization algorithm and hardware implementation is presented to compute quantized coefficient for six different video codecs including the new developing codec High Efficiency Video Coding (HEVC). HEVC, successor to H.264/MPEG-4 AVC, aims to substantially improve coding efficiency compared to AVC High Profile. The thesis presents a high performance circuit shared architecture that can perform the quantization operation for HEVC, H.264/AVC, AVS, VC-1, MPEG- 2/4 and Motion JPEG (MJPEG). Since HEVC is still in drafting stage, the architecture was designed in such a way that any final changes can be accommodated into the design. The proposed quantizer architecture is completely division free as the division operation is replaced by multiplication, shift and addition operations. The design was implemented on FPGA and later synthesized in CMOS 0.18 μm technology. The results show that the proposed design satisfies the requirement of all codecs with a maximum decoding capability of 60 fps at 187.3 MHz for Xilinx Virtex4 LX60 FPGA of a 1080p HD video. The scheme is also suitable for low-cost implementation in modern multi-codec systems

The 1993 Space and Earth Science Data Compression Workshop

The Earth Observing System Data and Information System (EOSDIS) is described in terms of its data volume, data rate, and data distribution requirements. Opportunities for data compression in EOSDIS are discussed

Efficient Encoding of Wireless Capsule Endoscopy Images Using Direct Compression of Colour Filter Array Images

Since its invention in 2001, wireless capsule endoscopy (WCE) has played an important role in the endoscopic examination of the gastrointestinal tract. During this period, WCE has undergone tremendous advances in technology, making it the first-line modality for diseases from bleeding to cancer in the small-bowel. Current research efforts are focused on evolving WCE to include functionality such as drug delivery, biopsy, and active locomotion. For the integration of these functionalities into WCE, two critical prerequisites are the image quality enhancement and the power consumption reduction. An efficient image compression solution is required to retain the highest image quality while reducing the transmission power. The issue is more challenging due to the fact that image sensors in WCE capture images in Bayer Colour filter array (CFA) format. Therefore, standard compression engines provide inferior compression performance. The focus of this thesis is to design an optimized image compression pipeline to encode the capsule endoscopic (CE) image efficiently in CFA format. To this end, this thesis proposes two image compression schemes. First, a lossless image compression algorithm is proposed consisting of an optimum reversible colour transformation, a low complexity prediction model, a corner clipping mechanism and a single context adaptive Golomb-Rice entropy encoder. The derivation of colour transformation that provides the best performance for a given prediction model is considered as an optimization problem. The low complexity prediction model works in raster order fashion and requires no buffer memory. The application of colour transformation yields lower inter-colour correlation and allows the efficient independent encoding of the colour components. The second compression scheme in this thesis is a lossy compression algorithm with a integer discrete cosine transformation at its core. Using the statistics obtained from a large dataset of CE image, an optimum colour transformation is derived using the principal component analysis (PCA). The transformed coefficients are quantized using optimized quantization table, which was designed with a focus to discard medically irrelevant information. A fast demosaicking algorithm is developed to reconstruct the colour image from the lossy CFA image in the decoder. Extensive experiments and comparisons with state-of-the-art lossless image compression methods establish the superiority of the proposed compression methods as simple and efficient image compression algorithm. The lossless algorithm can transmit the image in a lossless manner within the available bandwidth. On the other hand, performance evaluation of lossy compression algorithm indicates that it can deliver high quality images at low transmission power and low computation costs

RAPID CLOCK RECOVERY ALGORITHMS FOR DIGITAL MAGNETIC RECORDING AND DATA COMMUNICATIONS

SIGLEAvailable from British Library Document Supply Centre-DSC:DXN024293 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

Development and evaluation of packet video schemes

Reflecting the two tasks proposed for the current year, namely a feasibility study of simulating the NASA network, and a study of progressive transmission schemes, are presented. The view of the NASA network, gleaned from the various technical reports made available to use, is provided. Also included is a brief overview of how the current simulator could be modified to accomplish the goal of simulating the NASA network. As the material in this section would be the basis for the actual simulation, it is important to make sure that it is an accurate reflection of the requirements on the simulator. Brief descriptions of the set of progressive transmission algorithms selected for the study are contained. The results available in the literature were obtained under a variety of different assumptions, not all of which are stated. As such, the only way to compare the efficiency and the implementational complexity of the various algorithms is to simulate them