13072
Di Zhao
Mobile GPU computing, or System on Chip with embedded GPU (SoC GPU), becomes in great demand recently. Since these SoCs are designed for mobile devices with real-time applications such as image processing and video processing, high-efficient implementations of wavelet transform are essential for these chips. In this paper, we develop two SoC GPU based DWT: […]
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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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Zeng Fei, Chen Yumin
A high performance terrain data compression method is proposed based on discrete wavelet transform (DWT) and parallel run-length code. But the implementation of the schemes to solve these models in realistic scenarios imposes huge demands of computing power. Compute Unified Device Architecture (CUDA) programmed, Graphic Processing Units (GPUs) are rapidly becoming a major choice in […]
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Mohammad Wadood Majid, Golrokh Mirzaei, Mohsin M. Jamali
The discrete wavelet Transform (DWT) has been studied and developed in various scientific and engineering fields. Its multi-resolution and locality nature facilitates application required for progressiveness in capturing high-frequency details. However, when dealing with enormous data volume, the performance may drastically reduce. The multi-resolution sub-band encoding provided by DWT enables for higher compression ratios, and […]
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M. Ahmadvand, A. Ezhdehakosh
JPEG2000 has become one of the most rewarding image coding standards. It provides a practical set of features which weren’t necessarily available in the previous standards. The features were realized as a result of two new techniques, namely the Discrete Wavelet Transform (DWT), and Embedded Block Coding with Optimized Truncation (EBCOT). The complexity of EBCOT […]
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Dietmar Wippig, Bernd Klauer
The Discrete Wavelet Transform (DWT) is applied to various signal and image processing applications. However the computation is computational expense. Therefore plenty of approaches have been proposed to accelerate the computation. Graphics processing units (GPUs) can be used as stream processor to speed up the calculation of the DWT. In this paper, we present a […]
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Dietmar Wippig, Bernd Klauer
The Discrete Wavelet Transform (DWT) is used in several signal and image processing applications. Due to the computational expense various approaches have been proposed. One approach is using graphics processing units (GPUs) as stream processors to speed up the calculation of the DWT. This paper presents a GPU implementation of the translation-invariant wavelet transform computed […]
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Wladimir J. van der Laan, Jos B.T.M. Roerdink, Andrei C. Jalba
The discrete wavelet transform (DWT) has a wide range of applications from signal processing to video and image compression. This transform, by means of the lifting scheme, can be performed in a memory and computation efficient way on modern, programmable GPUs, which can be regarded as massively parallel co-processors through NVidia’s CUDA compute paradigm. The […]
Tien-Tsin Wong, Chi-Sing Leung, Pheng-Ann Heng, Jianqing Wang
Discrete wavelet transform (DWT) has been heavily studied and developed in various scientific and engineering fields. Its multiresolution and locality nature facilitates applications requiring progressiveness and capturing high-frequency details. However, when dealing with enormous data volume, its performance may drastically reduce. On the other hand, with the recent advances in consumer-level graphics hardware, personal computers […]

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