Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Rain Removal from Still Images Using Image Smoothing Filter and Morphological Filter


     

   Subscribe/Renew Journal


Removal of rain from still images is a complex and a challenging task. The rain drops affects only on a very small region of an image, and hence, leading to a confusion to determine which region should be considered and which should not. In this paper, a new technique has been implemented which effectively uses the gradient minimization approach to remove the rain pixels. The minimization technique can globally control how many non-zero gradients are resulted in the image. The method is independent of local features, but instead locates important edges globally. These salient edges are preserved and low amplitude and insignificant details are diminished. The rain pixels are removed in this manner. Finally the rain removed images are enhanced in intensity using histogram adjustment technique to get better contrast images. Experimental results show that the proposed algorithm is highly efficient as it removes rain effectively even under heavy rain conditions, while preserving the details of the image.


Keywords

Rain Removal; Gradient Minimization; Smoothing; Connected Components
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 205

PDF Views: 0




  • Rain Removal from Still Images Using Image Smoothing Filter and Morphological Filter

Abstract Views: 205  |  PDF Views: 0

Authors

Abstract


Removal of rain from still images is a complex and a challenging task. The rain drops affects only on a very small region of an image, and hence, leading to a confusion to determine which region should be considered and which should not. In this paper, a new technique has been implemented which effectively uses the gradient minimization approach to remove the rain pixels. The minimization technique can globally control how many non-zero gradients are resulted in the image. The method is independent of local features, but instead locates important edges globally. These salient edges are preserved and low amplitude and insignificant details are diminished. The rain pixels are removed in this manner. Finally the rain removed images are enhanced in intensity using histogram adjustment technique to get better contrast images. Experimental results show that the proposed algorithm is highly efficient as it removes rain effectively even under heavy rain conditions, while preserving the details of the image.


Keywords


Rain Removal; Gradient Minimization; Smoothing; Connected Components