scholarly journals Coastal Visibility Distance Estimation Using Dark Channel Prior and Distance Map Under Sea-Fog: Korean Peninsula Case

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4432
Author(s):  
Tae Wuk Bae ◽  
Jin Hyun Han ◽  
Kuk Jin Kim ◽  
Young Taeg Kim
Keyword(s):  
Estimation Method ◽  
Distance Estimation ◽  
Local Limit ◽  
Wide Area ◽  
Dark Channel Prior ◽  
Distance Map ◽  
Sea Fog ◽  
Visibility Distance ◽  
Sensor Structure ◽  
Dark Channel

Commercial visibility sensors among meteorological sensors estimate the visibility distance based on transmission, backward scattering, and forward scattering principle. These optical visibility sensors yield comparatively accurate local visibility distance. However, it is still difficult to obtain comprehensive visibility information for a wide area, such as the coast or harbor due to the sensor structure using straightness and scattering properties of light. In this paper, we propose a novel visibility distance estimation method using dark channel prior (DCP) and distance map based on a camera image. The proposed method improves the local limit of optical visibility sensor and detects the visibility distance of a wide area more precisely. First, the dark channel for an input sea-fog image is calculated. The binary transmission image is obtained by applying a threshold to the estimated transmission from the dark channel. Then, the sum of the distance values of pixels, corresponding to the sea-fog boundary, is averaged, in order to derive the visibility distance. This paper also proposes a novel air-light and transmission estimation technique in order to extract the visibility distance for an abnormal sea-fog image, including any light source, such as sunlight, reflection light, and illumination light, etc. The estimated visibility distance was compared with optical visibility distance of an optical visibility sensor and their agreement was evaluated.

scholarly journals Dehazing with Offset Correction and a Weighted Residual Map

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1419
Author(s):  
Chang Su ◽  
Wensheng Wang ◽  
Xingxiang Zhang ◽  
Longxu Jin
Keyword(s):  
Image Quality ◽  
Estimation Method ◽  
Expected Value ◽  
Experimental Results ◽  
Dark Channel Prior ◽  
Image Information ◽  
Dark Channel ◽  
Offset Correction ◽  
Transmission Estimation

In hazy environments, image quality is degraded by haze and the degraded photos have reduced visibility, making the less vivid and visually attractive. This paper proposes a method for recovering image information from a single hazy image. The dark channel prior algorithm tends to underestimate the transmission of bright areas. To address this problem, an improved dehazing algorithm is proposed in this paper. Assuming that intensity in a dark channel affected by haze produces the same offset, the expected value of the dark channel of a hazy image is used as an approximation of this offset to correct the transmission. However, this correction may neglect scene difference and affect the clarity of the recovered images. Therefore, a weighted residual map is used to enhance contrast and recover more information. Experimental results demonstrate that our algorithm can effectively lessen color oversaturation and restore images with enhanced details. This algorithm provides a more accurate transmission estimation method that can be used with a weighted residual map to eliminate haze and improve contrast.

Real-time visibility distance evaluation based on monocular and dark channel prior

2015 ◽  
Vol 10 (4) ◽  
pp. 375
Author(s):  
Hongjun Song ◽  
Yangzhou Chen ◽  
Yuanyuan Gao
Keyword(s):  
Real Time ◽  
Dark Channel Prior ◽  
Visibility Distance ◽  
Dark Channel

scholarly journals Specular Reflection Image Enhancement Based on a Dark Channel Prior

2021 ◽  
Vol 13 (1) ◽  
pp. 1-11
Author(s):  
Ye Xin ◽  
Zhenhong Jia ◽  
Jie Yang ◽  
Nikola K. Kasabov
Keyword(s):  
Image Enhancement ◽  
Specular Reflection ◽  
Dark Channel Prior ◽  
Dark Channel ◽  
Reflection Image

An improved image blind deblurring based on dark channel prior

2021 ◽  
Vol 17 (1) ◽  
pp. 40-46
Author(s):  
Man-wei Wang ◽  
Fu-zhen Zhu ◽  
Yu-yang Bai
Keyword(s):  
Dark Channel Prior ◽  
Blind Deblurring ◽  
Dark Channel

scholarly journals A Fast Single-Image Dehazing Algorithm Based on Dark Channel Prior and Rayleigh Scattering

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 73330-73339 ◽  
Author(s):  
Jehoiada Jackson ◽  
She Kun ◽  
Kwame Obour Agyekum ◽  
Ariyo Oluwasanmi ◽  
Parinya Suwansrikham
Keyword(s):  
Rayleigh Scattering ◽  
Dark Channel Prior ◽  
Single Image ◽  
Image Dehazing ◽  
Dark Channel ◽  
Single Image Dehazing

scholarly journals An image dehazing algorithm based on double priors constraint

2018 ◽  
Vol 189 ◽  
pp. 04009
Author(s):  
Kun Liu ◽  
Shiping Wang ◽  
Linyuan He ◽  
Duyan Bi ◽  
Shan Gao
Keyword(s):  
Standard Deviation ◽  
Mean Value ◽  
Experimental Results ◽  
Dark Channel Prior ◽  
Image Dehazing ◽  
Color Distortion ◽  
Local Media ◽  
Dark Channel

Aiming at the color distortion of the restored image in the sky region, we propose an image dehazing algorithm based on double priors constraint. Firstly, we divided the haze image into sky and non-sky regions. Then the Color-lines prior and dark channel prior are used for estimating the transmission of sky and non-sky regions respectively. After introducing color-lines prior to correct sky regions restored by the dark channel prior, we get an accurate transmission. Finally, the local media mean value and standard deviation are used to refine the transmission to obtain the dehazing image. Experimental results show that the algorithm has obvious advantages in the recovery of the sky area.

scholarly journals Restoration and Enhancement of Underwater Images Based on Bright Channel Prior

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Yakun Gao ◽  
Haibin Li ◽  
Shuhuan Wen
Keyword(s):  
Histogram Equalization ◽  
New Method ◽  
Dark Channel Prior ◽  
Image Dehazing ◽  
Underwater Environment ◽  
Dark Channel ◽  
Bright Channel Prior ◽  
Channel Image ◽  
Atmospheric Light

This paper proposed a new method of underwater images restoration and enhancement which was inspired by the dark channel prior in image dehazing field. Firstly, we proposed the bright channel prior of underwater environment. By estimating and rectifying the bright channel image, estimating the atmospheric light, and estimating and refining the transmittance image, eventually underwater images were restored. Secondly, in order to rectify the color distortion, the restoration images were equalized by using the deduced histogram equalization. The experiment results showed that the proposed method could enhance the quality of underwater images effectively.

Genetic Algorithm-based Dark Channel Prior Parameters Selection for Single Underwater Image Dehazing

2020 ◽  
Author(s):  
Vincent Jan D. Almero ◽  
Ronnie S. Concepcion ◽  
Jonnel D. Alejandrino ◽  
Argel A. Bandala ◽  
Jason L. Espanola ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Dark Channel Prior ◽  
Image Dehazing ◽  
Underwater Image ◽  
Parameters Selection ◽  
Dark Channel ◽  
Selection For
Sign in / Sign up

Export Citation Format

Share Document