Contourlet变换和遗传算法相结合的沥青红外图像增强方法

doi:10.3969/j.issn.1000-1158.2019.01.05

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Abstract As the construction process of asphalt, the collected infrared images are susceptible to the ambient noise, making the image blurred and the SNR low, which leads to decrease the accuracy of the subsequent image processing analysis. Basing on the noise characteristic, a method of combining contourlet transform with genetic algorithm of infrared image enhancement are proposed. Firstly, the original infrared image is subjected to contourlet transform, and the bandpass subband with the multi-scale and multi-directional information is obtained. Then, the bandpass subband carries on the fuzzy enhancement.The fuzzy enhancement parameters are optimized by adaptive genetic algorithm. Finally, the contourlet inverse transform is used in the enhanced bandpass subband, obtain the enhanced infrared image. The experimental results show that compared with other commonly used infrared image enhancement methods, this method can effectively suppress the noise, improve the clarity, and achieve a better enhancement effect.

Key words： metrology infrared image enhancement image processing contourlet transform genetic algorithm

Received: 02 March 2017 Published: 07 January 2019

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TB942

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	Articles by authors
	ZHU Dan-dan
	WANG Bin
	YANG Yi
	LI Yong-bo

Cite this article:

ZHU Dan-dan,WANG Bin,YANG Yi, et al. Asphalt Infrared Image Enhancement of Combining Contourlet Transform with Genetic Algorithm[J]. Acta Metrologica Sinica, 2019, 40(1): 25-30.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2019.01.05 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2019/V40/I1/25

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