Biologically inspired image enhancement based on Retinex

	Biologically inspired image enhancement based on Retinex
	Wang, Y. F.; H. Y. Wang; C. L. Yin and M. Dai
	2016
发表期刊	Neurocomputing
卷号	177
摘要	For the nonlinear and non-stationary signals existing in a MEMS (Micro-electronic-mechanic system) gyro, a denosing method based on the Empirical Mode Decomposition/High Order Statistic (EMD/HOS) was proposed. Firstly, the MEMS gyro signals were captured, and they were decomposed into a cluster of intrinsic mode function (IMF) based on the proposed EMD/HOS sift process. The IMF peak values were estimated by using Bootstrap technology, respectively, to verify its Gaussianity and the Gaussian components were filtered directly. Then the variance algorithm was used to calculate the Hurst exponent of the IMF. According to the Hurst exponent, the threshold was calculated and the each IMF was processed by soft threshold technology. Finally, the remained IMFs after threshold processing were reconstructed to implement the signal denoise. Moreover, the Allan variance algorithm was introduced to analyze the gyro noise, and the characteristic of gyro noise could be observed via the curve of related time and root Allan variance. The conclusion is that EMD-HOS and soft threshold technology decrease the noise of MEMS obviously, the SNR is increased by 5.6 dB, and each indicator of MEMS; gyro noise is improved almost by one order. 2016, Chinese Academy of Sciences. All right reserved.
文章类型	期刊
收录类别	SCI ; EI
语种	英语
文献类型	期刊论文
条目标识符	http://ir.ciomp.ac.cn/handle/181722/57267
专题	中科院长春光机所知识产出
推荐引用方式 GB/T 7714	Wang, Y. F.,H. Y. Wang,C. L. Yin and M. Dai. Biologically inspired image enhancement based on Retinex[J]. Neurocomputing,2016,177.
APA	Wang, Y. F.,H. Y. Wang,&C. L. Yin and M. Dai.(2016).Biologically inspired image enhancement based on Retinex.Neurocomputing,177.
MLA	Wang, Y. F.,et al."Biologically inspired image enhancement based on Retinex".Neurocomputing 177(2016).

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