Image and video dehazing using view-based cluster segmentation
2016 Visual Communications and Image Processing (VCIP), 2016•ieeexplore.ieee.org
To avoid distortion in sky regions and make the sky and white objects clear, in this paper we
propose a new image and video dehazing method utilizing the view-based cluster
segmentation. Firstly, GMM (Gaussian Mixture Model) is utilized to cluster the depth map
based on the distant view to estimate the sky region and then the transmission estimation is
modified to reduce distortion. Secondly, we present to use GMM based on Color Attenuation
Prior to divide a single hazy image into K classifications, so that the atmospheric light …
propose a new image and video dehazing method utilizing the view-based cluster
segmentation. Firstly, GMM (Gaussian Mixture Model) is utilized to cluster the depth map
based on the distant view to estimate the sky region and then the transmission estimation is
modified to reduce distortion. Secondly, we present to use GMM based on Color Attenuation
Prior to divide a single hazy image into K classifications, so that the atmospheric light …
To avoid distortion in sky regions and make the sky and white objects clear, in this paper we propose a new image and video dehazing method utilizing the view-based cluster segmentation. Firstly, GMM(Gaussian Mixture Model)is utilized to cluster the depth map based on the distant view to estimate the sky region and then the transmission estimation is modified to reduce distortion. Secondly, we present to use GMM based on Color Attenuation Prior to divide a single hazy image into K classifications, so that the atmospheric light estimation is refined to improve global contrast. Finally, online GMM cluster is applied to video dehazing. Extensive experimental results demonstrate that the proposed algorithm can have superior haze removing and color balancing capabilities.
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