Abstract
Foggy images suffer from low contrast and poor visibility problem along with little color information of the scene. It is imperative to remove fog from images as a pre-processing step in computer vision. The Dark Channel Prior (DCP) technique is a very promising defogging technique due to excellent restoring results for images containing no homogeneous region. However, having a large homogeneous region such as sky region, the restored images suffer from color distortion and block effects. Thus, to overcome the limitation of DCP method, we introduce a framework which is based on sky and non-sky region segmentation and restoring sky and non-sky parts separately. Here, isolation of the sky and non-sky part is done by using a binary mask formulated by floodfill algorithm. The foggy sky part is restored by using Contrast Limited Adaptive Histogram Equalization (CLAHE) and non-sky part by modified DCP. The restored parts are blended together for the resultant image. The proposed method is evaluated using both synthetic and real world foggy images against state of the art techniques. The experimental result shows that our proposed method provides better entropy value than other stated techniques along with have better natural visual effects while consuming much lower processing time.
Highlights
During bad weather, the presence of fog in the atmosphere reduces perception of visibility
Since multiple image-based methods are not effective, single image fog removal methods have become more popular. This can be done in two different ways: the techniques based on image enhancement and other on image restoration
Though color distortion and halo effects in sky region due to Dark Channel Prior (DCP) are eliminated, this method cannot preserve the original color of the sky region. To eliminate this issue regarding the distortion of sky region while using DCP, we proposed a method based on partitioning the sky portion and restoring the non-sky and sky part individually
Summary
The presence of fog in the atmosphere reduces perception of visibility. Since multiple image-based methods are not effective, single image fog removal methods have become more popular This can be done in two different ways: the techniques based on image enhancement and other on image restoration. The proposed method restores the foggy image in an efficient way and requires much less computational time as compared to other techniques. It restores the original color of the initial foggy image. This method does not require any prior knowledge about the feature of each isolated image, can be used to defog images having different characteristics.
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