基于GPU的多尺度Retinex图像增强算法实现

doi:10.3976/j.issn.1002-4026.2017.03.018

Abstract

Abstract:

To improve the realtime performance of the multiscale Retinex algorithm, a GPU based multiscale Retinex image enhancement algorithm was proposed in this paper. Through the data analysis and parallel mining of the algorithm, timeconsuming modules of the calculation, such as Gauss filter, convolution, and logarithm difference, were implemented in GPU, and the efficiency was improved by using massively parallel processing threads. Experiments were conducted in GeForce GTX 480 and CUDA5.5, and the results showed that the proposed algorithm could significantly improve the computing speed, and with the increasing of the image resolution, the maximum speed up ratio could reach 160 times.

Key words: multi-scale Retinex, parallel computing, GPU, image enhancement, CUDA

CLC Number:

TP391.41

LI Hui, XIE Wei-hao, LIU Shou-sheng, GAI Ying-ying. Realization of multiscale Retinex image enhancement algorithm based on GPU[J].SHANDONG SCIENCE, 2017, 30(3): 103-109.

References

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Realization of multiscale Retinex image enhancement algorithm based on GPU

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