Abstract
Image haze removal using dark channel prior is prone to encountering color distortion in sky and brightness region. To solve the problem, we proposed an improved method based on inverse image and dark channel prior. Firstly, we applied inverse image to estimating a new transmission map. The new transmission map can be used to modify original transmission map in order to avoid color distortion. Next, fast guider filter was applied to refining transmission map. Using the transmission map, we can recover a high quality haze-free image. Experimental results showed that the proposed method is feasible, and visibility can be enhanced.
Highlights
The contrast and visibility of the haze images are all decreased, which directly affects the air, water and road transport
Tan et al [4] maximized the contrast of a hazy image, assuming that the haze-free image has a higher contrast than the hazy image
By optimizing the cost function, the proposed algorithm can enhance the contrast and preserve the information optimally. He et al [7] proposed a single image haze removal based on Dark Channel Prior (DCP)
Summary
The contrast and visibility of the haze images are all decreased, which directly affects the air, water and road transport. Fattal et al [5] decomposed the scene radiance of an image into the albedo and the shading, and estimated the scene radiance, assuming that the shading and the object depth are locally uncorrelated. It can remove haze locally but cannot restore densely hazy images. By optimizing the cost function, the proposed algorithm can enhance the contrast and preserve the information optimally. He et al [7] proposed a single image haze removal based on Dark Channel Prior (DCP). We proposed an improved method based on [7] to deal with this case
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