Image parallel processing based on GPU

In order to solve the compute-intensive character of image processing, based on advantages of GPU parallel operation, parallel acceleration processing technique is proposed for image. First, efficient architecture of GPU is introduced that improves computational efficiency, comparing with CPU. Then,...

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Vydáno v:2010 2nd International Conference on Advanced Computer Control Ročník 3; s. 367 - 370
Hlavní autoři: Nan Zhang, Yun-shan Chen, Jian-li Wang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.03.2010
Témata:
Acceleration
Computational efficiency
Computer architecture
Concurrent computing
CUDA
Detectors
Filtering algorithms
GPU
Image edge detection
Image processing
Parallel operation
Parallel processing
Testing
ISBN:1424458455, 9781424458455
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Popis
Shrnutí:In order to solve the compute-intensive character of image processing, based on advantages of GPU parallel operation, parallel acceleration processing technique is proposed for image. First, efficient architecture of GPU is introduced that improves computational efficiency, comparing with CPU. Then, Sobel edge detector and homomorphic filtering, two representative image processing algorithms, are embedded into GPU to validate the technique. Finally, tested image data of different resolutions are used on CPU and GPU hardware platform to compare computational efficiency of GPU and CPU. Experimental results indicate that if data transfer time, between host memory and device memory, is taken into account, speed of the two algorithms implemented on GPU can be improved approximately 25 times and 49 times as fast as CPU, respectively, and GPU is practical for image processing.
ISBN:1424458455
9781424458455
DOI:10.1109/ICACC.2010.5486836