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第30届中国控制与决策会议

作者： Shibing Ye Zhixing Niu Peng Yang Junqing Sun Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology

Based on laser induced breakdown spectroscopy（LIBS） technique, the content of the main elements in the liquid steel of carbon steel alloy can be detected in real time during melting process. In order to detect the liquid alloy steel and forecast the content of the main elements in the alloy steel more accurately, we use the method of sparse autoencoder to reduce noise in the spectral data which were collected in the detecting process. The experimental results show that the sparse autoencoder method can effectively improve the accuracy and precision of the spectral data.

关键词： LIBS sparse autoencoder spectral data denosing

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An Improved Image Denoising Method Based on Wavelet Thresholding

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Journal of Signal and Information Processing 2012年第1期3卷 109-116页

作者： Hari Om Mantosh Biswas Department of Computer Science & Engineering Indian School of Mines Dhanbad India.

VisuShrink, ModineighShrink and NeighShrink are efficient image denoising algorithms based on the discrete wavelet transform (DWT). These methods have disadvantage of using a suboptimal universal threshold and identical neighbouring window size in all wavelet subbands. In this paper, an improved method is proposed, that determines a threshold as well as neighbouring window size for every subband using its lengths. Our experimental results illustrate that the proposed approach is better than the existing ones, i.e., NeighShrink, ModineighShrink and VisuShrink in terms of peak signal-to-noise ratio (PSNR) i.e. visual quality of the image.

关键词： Wavelet Transforms Neighboring Coefficients Wavelet Thresholding Image denosing Neighbouring Coefficients Peak Signal-to-Noise Ratio

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Research on Destriping Based on Rough Set

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Journal of Computer and Communications 2015年第11期3卷 8-12页

作者： Xiangyang Chen Liping Chen Sile Wang Wenzhu Yang Sukui Lu School of Computer Science and Technology Hebei University Baoding China

In order to remove the stripe noises in cotton foreign fiber images by line scanning camera collected, in multi threshold segmentation of rough set, every region’s color is instead of the statistics color of the region. This method can retain the detail information of original image as far as possible, and do well in the stripe noise removal. The roughness of rough set was calculated respectively using directional diagram, Canny operator and Sobel operator. Comparing the three methods, the results indicate that the Canny operator keeps the more details of image, and directional diagram and Sobel operator have the better effects on denoising.

关键词： Stripe Noises Multi Threshold Segmentation Rough Set denosing

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