Haze Density Estimation and Dark Channel Prior Based Image Defogging

2018 ◽  
Author(s):  
Rujun Li ◽  
U Kintak
Keyword(s):  
Density Estimation ◽  
Dark Channel Prior ◽  
Image Defogging ◽  
Dark Channel

An improved dark channel prior image defogging algorithm based on wavelength compensation

2019 ◽  
Vol 12 (4) ◽  
pp. 501-512
Author(s):  
Zhixiang Chen ◽  
Binna Ou ◽  
Qianyi Tian
Keyword(s):  
Dark Channel Prior ◽  
Image Defogging ◽  
Dark Channel

Nighttime Image Defogging Based on the Theory of Retinex and Dark Channel Prior

2017 ◽  
Vol 54 (4) ◽  
pp. 041002 ◽  
Author(s):  
杨爱萍 Yang Aiping ◽  
白煌煌 Bai Huanghuang
Keyword(s):  
Dark Channel Prior ◽  
Image Defogging ◽  
Dark Channel ◽  
Nighttime Image

scholarly journals Incident Light Frequency-Based Image Defogging Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Wenbo Zhang ◽  
Xiaorong Hou
Keyword(s):  
Incident Light ◽  
Input Image ◽  
Dark Channel Prior ◽  
Improved Method ◽  
Color Channel ◽  
Original Algorithm ◽  
Image Defogging ◽  
Dark Channel ◽  
Natural Result ◽  
Improved Algorithm

To solve the color distortion problem produced by the dark channel prior algorithm, an improved method for calculating transmittance of all channels, respectively, was proposed in this paper. Based on the Beer-Lambert Law, the influence between the frequency of the incident light and the transmittance was analyzed, and the ratios between each channel’s transmittance were derived. Then, in order to increase efficiency, the input image was resized to a smaller size before acquiring the refined transmittance which will be resized to the same size of original image. Finally, all the transmittances were obtained with the help of the proportion between each color channel, and then they were used to restore the defogging image. Experiments suggest that the improved algorithm can produce a much more natural result image in comparison with original algorithm, which means the problem of high color saturation was eliminated. What is more, the improved algorithm speeds up by four to nine times compared to the original algorithm.

scholarly journals Improved Dark Channel Prior for Image Defogging Using RGB and YCbCr Color Space

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 32576-32587 ◽  
Author(s):  
Zahid Tufail ◽  
Khawar Khurshid ◽  
Ahmad Salman ◽  
Imran Fareed Nizami ◽  
Khurram Khurshid ◽  
...  
Keyword(s):  
Color Space ◽  
Dark Channel Prior ◽  
Ycbcr Color Space ◽  
Image Defogging ◽  
Dark Channel

scholarly journals An Improved DCP-Based Image Defogging Algorithm Combined with Adaptive Fusion Strategy

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zhou Fang ◽  
Qilin Wu ◽  
Darong Huang ◽  
Dashuai Guan
Keyword(s):  
State Of The Art ◽  
Logistic Function ◽  
Dark Channel Prior ◽  
Single Image ◽  
Fusion Strategy ◽  
Image Defogging ◽  
Satisfactory Performance ◽  
Dark Channel ◽  
Adaptive Fusion ◽  
Simple Implementation

Dark channel prior (DCP) has been widely used in single image defogging because of its simple implementation and satisfactory performance. This paper addresses the shortcomings of the DCP-based defogging algorithm and proposes an optimized method by using an adaptive fusion mechanism. This proposed method makes full use of the smoothing and “squeezing” characteristics of the Logistic Function to obtain more reasonable dark channels avoiding further refining the transmission map. In addition, a maximum filtering on dark channels is taken to improve the accuracy of dark channels around the object boundaries and the overall brightness of the defogged clear images. Meanwhile, the location information and brightness information of fog image are weighed to obtain more accurate atmosphere light. Quantitative and qualitative comparisons show that the proposed method outperforms state-of-the-art image defogging algorithms.

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