目的因为有雨图像中雨线存在方向、密度和大小等各方面的差异,单幅图像去雨依旧是一个充满挑战的研究问题。现有算法在某些复杂图像上仍存在过度去雨或去雨不足等问题,部分复杂图像的边缘高频信息在去雨过程中被抹除,或图像中残留雨成...目的因为有雨图像中雨线存在方向、密度和大小等各方面的差异,单幅图像去雨依旧是一个充满挑战的研究问题。现有算法在某些复杂图像上仍存在过度去雨或去雨不足等问题,部分复杂图像的边缘高频信息在去雨过程中被抹除,或图像中残留雨成分。针对上述问题,本文提出三维注意力和Transformer去雨网络(three-dimension attention and Transformer deraining network,TDATDN)。方法将三维注意力机制与残差密集块结构相结合,以解决残差密集块通道高维度特征融合问题;使用Transformer计算特征全局关联性;针对去雨过程中图像高频信息被破坏和结构信息被抹除的问题,将多尺度结构相似性损失与常用图像去雨损失函数结合参与去雨网络训练。结果本文将提出的TDATDN网络在Rain12000雨线数据集上进行实验。其中,峰值信噪比(peak signal to noise ratio,PSNR)达到33.01 d B,结构相似性(structural similarity,SSIM)达到0.9278。实验结果表明,本文算法对比以往基于深度学习的神经网络去雨算法,显著改善了单幅图像去雨效果。结论本文提出的TDATDN图像去雨网络结合了3D注意力机制、Transformer和编码器—解码器架构的优点,可较好地完成单幅图像去雨工作。展开更多
Due to link additions, small world phenomena exist in tree-based wireless sensor networks. Epidemics on small worlds of tree-based networks are studied, and the epidemic threshold at which the outbreak of the epideIrl...Due to link additions, small world phenomena exist in tree-based wireless sensor networks. Epidemics on small worlds of tree-based networks are studied, and the epidemic threshold at which the outbreak of the epideIrlic occurs is calculated. Epidemiological processes are analyzed when the infection probability is larger than the percolation threshold. Although different epidemiological processes occur on the underlying tree topology, the number of infected nodes increases exponentially as the infection spreads. The uniform immunization procedure is conducted in the homogeneous small-world network. The infection still extends exponentially Mthough the immunization effectively reduces the prevalence speed.展开更多
文摘目的因为有雨图像中雨线存在方向、密度和大小等各方面的差异,单幅图像去雨依旧是一个充满挑战的研究问题。现有算法在某些复杂图像上仍存在过度去雨或去雨不足等问题,部分复杂图像的边缘高频信息在去雨过程中被抹除,或图像中残留雨成分。针对上述问题,本文提出三维注意力和Transformer去雨网络(three-dimension attention and Transformer deraining network,TDATDN)。方法将三维注意力机制与残差密集块结构相结合,以解决残差密集块通道高维度特征融合问题;使用Transformer计算特征全局关联性;针对去雨过程中图像高频信息被破坏和结构信息被抹除的问题,将多尺度结构相似性损失与常用图像去雨损失函数结合参与去雨网络训练。结果本文将提出的TDATDN网络在Rain12000雨线数据集上进行实验。其中,峰值信噪比(peak signal to noise ratio,PSNR)达到33.01 d B,结构相似性(structural similarity,SSIM)达到0.9278。实验结果表明,本文算法对比以往基于深度学习的神经网络去雨算法,显著改善了单幅图像去雨效果。结论本文提出的TDATDN图像去雨网络结合了3D注意力机制、Transformer和编码器—解码器架构的优点,可较好地完成单幅图像去雨工作。
基金supported by the National Natural Science Foundation of China under Grant No.61203144the General Financial Grant from the China Postdoctoral Science Foundation under Grant No.2013M540869the Open Fund of Guangdong Provincial Digital Signal and Image Processing Technologies Key Laboratory under Grant No.2013GDDSIPL-06
文摘Due to link additions, small world phenomena exist in tree-based wireless sensor networks. Epidemics on small worlds of tree-based networks are studied, and the epidemic threshold at which the outbreak of the epideIrlic occurs is calculated. Epidemiological processes are analyzed when the infection probability is larger than the percolation threshold. Although different epidemiological processes occur on the underlying tree topology, the number of infected nodes increases exponentially as the infection spreads. The uniform immunization procedure is conducted in the homogeneous small-world network. The infection still extends exponentially Mthough the immunization effectively reduces the prevalence speed.
