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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Bibliographic Details
Published in:2010 2nd International Conference on Advanced Computer Control Vol. 3; pp. 367 - 370
Main Authors: Nan Zhang, Yun-shan Chen, Jian-li Wang
Format: Conference Proceeding
Language:English
Published: IEEE 01.03.2010
Subjects:
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
Online Access:Get full text
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Summary: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