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Content Provider | IEEE Xplore Digital Library |
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Author | Quan, Tran Minh Jeong, Won-Ki |
Copyright Year | 2014 |
Description | Author affiliation: School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, South Korea (Quan, Tran Minh; Jeong, Won-Ki) |
Abstract | 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, we observe that rearranging the spatial locations of wavelet coefficients at every level of DWT significantly impairs the performance of memory transaction on the GPU. To address these problems, we propose a mixed-band lifting wavelet transform that reduces uncoalesced global memory access on the GPU and maximizes on-chip memory bandwidth by implementing in-place operations using registers. We assess the performance of the proposed method by comparing with the state-of-the-art DWT libraries, and show its usability in a compressive sensing (CS) MRI application. |
Starting Page | 1238 |
Ending Page | 1242 |
File Size | 454537 |
Page Count | 5 |
File Format | |
ISBN | 9781479957514 |
DOI | 10.1109/ICIP.2014.7025247 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-10-27 |
Publisher Place | France |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Graphics processing units Three-dimensional displays Image reconstruction Discrete wavelet transforms Magnetic resonance imaging MRI Mixed-band Wavelet Denoising CUDA GPU Parallel Computing Compressive Sensing |
Content Type | Text |
Resource Type | Article |
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