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Jose M Gonzalez-Linares, Antonio Fuentes-Alventosa, Juan Gomez-Luna, Nicolas Guil
Data compression is the process of representing information in a compact form, in order to reduce the storage requirements and, hence, communication bandwidth. It has been one of the critical enabling technologies for the ongoing digital multimedia revolution for decades. In the variable-length encoding (VLE) compression method, most frequently occurring symbols are replaced by codes […]
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Piotr Przymus
In recent years, processing and exploration of time series has experienced a noticeable interest. Growing volumes of data and needs of efficient processing pushed the research in new directions, including hardware based solutions. Graphics Processing Units (GPU) have significantly more applications than just rendering images. They are also used in general purpose computing to solve […]
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Nathalie Kaligirwa, Eleazar Leal, Le Gruenwald, Jianting Zhang, Simin You
Global remote sensing and large-scale environment modeling have generated vast amounts of raster geospatial images. To gain a better understanding of this data, researchers are interested in performing spatial queries over them, and the computation of those queries’ results is greatly facilitated by the existence of spatial indices. Additionally, though there have been major advances […]
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John Ashley, Amy J. Braverman
Multi-trial sampled K-means performance and scalability is studied as a stepping stone towards a Graphical Processing Unit implementation of Entropy Constrained Vector Quantization for interactive data compression. Basic parallelization strategies and data layout impacts are explored with K-means. The K-means implementation is extended to Entropy Constrained Vector Quantization, and additional tuning specific to the anticipated […]
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Bryan Ching
Lossless data compression is used to reduce storage requirements, allowing for the relief of I/O channels and better utilization of bandwidth. The Lempel-Ziv lossless compression algorithms form the basis for many of the most commonly used compression schemes. General purpose computing on graphic processing units (GPGPUs) allows us to take advantage of the massively parallel […]
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Jason J. Ford, Timothy L. Molloy, Joanne L. Hall
This paper investigates compressed sensing using hidden Markov models (HMMs) and hence provides an extension of recent single frame, bounded error sparse decoding problems into a class of sparse estimation problems containing both temporal evolution and stochastic aspects. This paper presents two optimal estimators for compressed HMMs. The impact of measurement compression on HMM filtering […]
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Aditya Deshpande
In earlier times, computer systems had only a single core or processor. In these computers, the number of transistors on-chip (i.e. on the processor) doubled every two years and all applications enjoyed free speedup. Subsequently, with more and more transistors being packed on-chip, power consumption became an issue, frequency scaling reached its limits and industry […]
Jingqi Ao
Lossless compression is still in high demand in medical image applications despite improvements in the computing capability and decrease in storage cost in recent years. With the development of General Purpose Graphic Processing Unit (GPGPU) computing techniques, sequential lossless image compression algorithms can be modified to achieve more efficiency and speed. Backward Coding of Wavelet […]
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Andrew A. Haigh, Eric C. McCreath
The realistic simulation of ultrasound wave propagation is computationally intensive. The large size of the grid and low degree of reuse of data means that it places a great demand on memory bandwidth. Graphics Processing Units (GPUs) have attracted attention for performing scientific calculations due to their potential for efficiently performing large numbers of floating […]
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Tran Minh Quan, Won-Ki Jeong
Discrete wavelet transform (DWT) has been widely used in many image compression applications, such as JPEG2000 and compressive sensing MRI. Even though a lifting scheme [1] has been widely adopted to accelerate DWT, only a handful of research has been done on its efficient implementation on many-core accelerators, such as graphics processing units (GPUs). Moreover, […]
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Hovhannes M. Bantikyan
The discrete wavelet transform has a huge number of applications in science, engineering, mathematics and computer science. Most notably, it is used for signal coding to represent a discrete signal in a more redundant form, often as a preconditioning for data compression. Beginning in the 1990s, wavelets have been found to be a powerful tool […]
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H.M. Magboub, M.A. Osman
This paper investigates the use of the Compute Unified Device Architecture (CUDA) programming model to implement Discrete Wavelet Transform (DWT) based algorithm for efficient image compression. The PSNR (Peak Signal to Noise Ratio) is used to evaluate image reconstruction quality in this paper. The results are presented and discussed.
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