Data compression for full motion video transmission

Clearly transmission of visual information will be a major, if not dominant, factor in determining the requirements for, and assessing the performance of the Space Exploration Initiative (SEI) communications systems. Projected image/video requirements which are currently anticipated for SEI mission scenarios are presented. Based on this information and projected link performance figures, the image/video data compression requirements which would allow link closure are identified. Finally several approaches which could satisfy some of the compression requirements are presented and possible future approaches which show promise for more substantial compression performance improvement are discussed

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

Image compression and energy harvesting for energy constrained sensors

Title from PDF of title page, viewed on June 21, 2013Dissertation advisor: Walter D. Leon-SalasVitaIncludes bibliographic references (pages 176-[187])Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2013The advances in complementary metal-oxide-semiconductor (CMOS) technology have led to the integration of all components of electronic system into a single integrated circuit. Ultra-low power circuit techniques have reduced the power consumption of circuits. Moreover, solar cells with improved efficiency can be integrated on chip to harvest energy from sunlight. As a result of all the above, a new class of miniaturized electronic systems known as self-powered system on a chip has emerged. There is an increasing research interest in the area of self-powered devices which provide cost-effective solutions especially when these devices are used in the areas that changing or replacing batteries is too costly. Therefore, image compression and energy harvesting are studied in this dissertation. The integration of energy harvesting, image compression, and an image sensor on the same chip provides the energy source to charge a battery, reduces the data rate, and improves the performance of wireless image sensors. Integrated circuits of image compression, solar energy harvesting, and image sensors are studied, designed, and analyzed in this work. In this dissertation, a hybrid image sensor that can perform the tasks of sensing and energy harvesting is presented. Photodiodes of hybrid image sensor can be programmed as image sensors or energy harvesting cells. The hybrid image sensor can harvest energy in between frames, in sleep mode, and even when it is taking images. When sensing images and harvesting energy are both needed at the same time, some pixels have to work as sensing pixels, and the others have to work as solar cells. Since some pixels are devoted to harvest energy, the resolution of the image will be reduced. To preserve the resolution or to keep the fair resolution when a lot of energy collection is needed, image reconstruction algorithms and compressive sensing theory provide solutions to achieve a good image quality. On the other hand, when the battery has enough charge, image compression comes into the picture. Multiresolution decomposition image compression provides a way to compress image data in order to reduce the energy need from data transmission. The solution provided in this dissertation not only harvests energy but also saves energy resulting long lasting wireless sensors. The problem was first studied at the system level to identify the best system-level configuration which was then implemented on silicon. As a proof of concept, a 32 x 32 array of hybrid image sensor, a 32 x 32 array of image sensor with multiresolution decomposition compression, and a compressive sensing converter have been designed and fabricated in a standard 0.5 [micrometer] CMOS process. Printed circuit broads also have been designed to test and verify the proposed and fabricated chips. VHDL and Matlab codes were written to generate the proper signals to control, and read out data from chips. Image processing and recovery were carried out in Matlab. DC-DC converters were designed to boost the inherently low voltage output of the photodiodes. The DC-DC converter has also been improved to increase the efficiency of power transformation.Introduction -- Hybrid imager system and circuit design -- Hybrid imager energy harvesting and image acquisition results and discussion -- Detailed description and mathematical analysis for a circuit of energy harvesting using on-chip solar cells -- Multiresolution decomposition for lossless and near-lossless compression -- An incremental [sigma-delta] converter for compressive sensing -- Detailed description of a sigma-delta random demodulator converter architecture for compressive sensing applications -- Conclusion -- Appendix A. Chip pin-out -- Appendix B. Schematics -- Appendix C. Pictures of custom PC

Improved quality block-based low bit rate video coding.

The aim of this research is to develop algorithms for enhancing the subjective quality and coding efficiency of standard block-based video coders. In the past few years, numerous video coding standards based on motion-compensated block-transform structure have been established where block-based motion estimation is used for reducing the correlation between consecutive images and block transform is used for coding the resulting motion-compensated residual images. Due to the use of predictive differential coding and variable length coding techniques, the output data rate exhibits extreme fluctuations. A rate control algorithm is devised for achieving a stable output data rate. This rate control algorithm, which is essentially a bit-rate estimation algorithm, is then employed in a bit-allocation algorithm for improving the visual quality of the coded images, based on some prior knowledge of the images. Block-based hybrid coders achieve high compression ratio mainly due to the employment of a motion estimation and compensation stage in the coding process. The conventional bit-allocation strategy for these coders simply assigns the bits required by the motion vectors and the rest to the residual image. However, at very low bit-rates, this bit-allocation strategy is inadequate as the motion vector bits takes up a considerable portion of the total bit-rate. A rate-constrained selection algorithm is presented where an analysis-by-synthesis approach is used for choosing the best motion vectors in term of resulting bit rate and image quality. This selection algorithm is then implemented for mode selection. A simple algorithm based on the above-mentioned bit-rate estimation algorithm is developed for the latter to reduce the computational complexity. For very low bit-rate applications, it is well-known that block-based coders suffer from blocking artifacts. A coding mode is presented for reducing these annoying artifacts by coding a down-sampled version of the residual image with a smaller quantisation step size. Its applications for adaptive source/channel coding and for coding fast changing sequences are examined