Outdoor haze has adverse impact on outdoor image quality,including contrast loss and poor visibility.In this paper,a novel dehazing algorithm based on the decomposition strategy is proposed.It combines the advantages ...Outdoor haze has adverse impact on outdoor image quality,including contrast loss and poor visibility.In this paper,a novel dehazing algorithm based on the decomposition strategy is proposed.It combines the advantages of the two-dimensional variational mode decomposition(2DVMD)algorithm and dark channel prior.The original hazy image is adaptively decom-posed into low-frequency and high-frequency images according to the image frequency band by using the 2DVMD algorithm.The low-frequency image is dehazed by using the improved dark channel prior,and then fused with the high-frequency image.Furthermore,we optimize the atmospheric light and transmit-tance estimation method to obtain a defogging effect with richer details and stronger contrast.The proposed algorithm is com-pared with the existing advanced algorithms.Experiment results show that the proposed algorithm has better performance in comparison with the state-of-the-art algorithms.展开更多
现有的注意力机制仅增强特征图的通道或空间维度,未能充分捕捉细微视觉元素和多尺度特征变化。为解决此问题,提出一种基于局部分块与全局多尺度特征融合的注意力机制(patch and global multiscale attention,PGMA)。将特征图分割成多个...现有的注意力机制仅增强特征图的通道或空间维度,未能充分捕捉细微视觉元素和多尺度特征变化。为解决此问题,提出一种基于局部分块与全局多尺度特征融合的注意力机制(patch and global multiscale attention,PGMA)。将特征图分割成多个小块,分别计算这些小块的注意力得分,增强对局部信息的感知能力。使用一组空洞卷积计算整个特征图的得分,获得全局多尺度信息的权衡。实验中,将PGMA集成到U-Net、DeepLab、SegNet等语义分割网络中,有效提升了它们的分割性能。这表明PGMA在增强CNN性能方面优于当前主流方法。展开更多
基金supported by the National Defense Technology Advance Research Project of China(004040204).
文摘Outdoor haze has adverse impact on outdoor image quality,including contrast loss and poor visibility.In this paper,a novel dehazing algorithm based on the decomposition strategy is proposed.It combines the advantages of the two-dimensional variational mode decomposition(2DVMD)algorithm and dark channel prior.The original hazy image is adaptively decom-posed into low-frequency and high-frequency images according to the image frequency band by using the 2DVMD algorithm.The low-frequency image is dehazed by using the improved dark channel prior,and then fused with the high-frequency image.Furthermore,we optimize the atmospheric light and transmit-tance estimation method to obtain a defogging effect with richer details and stronger contrast.The proposed algorithm is com-pared with the existing advanced algorithms.Experiment results show that the proposed algorithm has better performance in comparison with the state-of-the-art algorithms.
文摘现有的注意力机制仅增强特征图的通道或空间维度,未能充分捕捉细微视觉元素和多尺度特征变化。为解决此问题,提出一种基于局部分块与全局多尺度特征融合的注意力机制(patch and global multiscale attention,PGMA)。将特征图分割成多个小块,分别计算这些小块的注意力得分,增强对局部信息的感知能力。使用一组空洞卷积计算整个特征图的得分,获得全局多尺度信息的权衡。实验中,将PGMA集成到U-Net、DeepLab、SegNet等语义分割网络中,有效提升了它们的分割性能。这表明PGMA在增强CNN性能方面优于当前主流方法。
