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.

Image Defogging Based on Improved Guided Image Filtering

2014 ◽  
Vol 536-537 ◽  
pp. 121-126
Author(s):  
Peng Fei Shen ◽  
Jie Yang ◽  
Yuan Yi Xiong
Keyword(s):  
Experimental Results ◽  
Dark Channel Prior ◽  
Improved Method ◽  
Visual Effect ◽  
Color Distortion ◽  
Image Defogging ◽  
Dark Channel ◽  
Guided Filtering ◽  
Guided Image Filtering ◽  
Estimated Error

In this paper, we analyze the principles of the dark channel prior based on guided filtering image algorithm to defog, pointing out the shortcomings and derive an improved method. Dark channel prior principle is established in the absence of bright areas, which not satisfied Dark channel prior, and thus, the transmittance of the bright areas is estimated error, which will case color distortion of defogged image. By introducing a tolerancemechanism refining the transmittance, the algorithm can effectively handle such problem to overcome the color distortion in bright areas using dark channel prior. Experimental results show that this modification is substantial practicable to restore image, at the same time eliminates the color distortion, significantly improve the visual effect.

Improved method for single image dehazing using dark channel prior

2016 ◽  
Vol 31 (8) ◽  
pp. 840-845 ◽  
Author(s):  
王凯 WANG Kai ◽  
王延杰 WANG Yan-jie ◽  
樊博 FAN Bo
Keyword(s):  
Dark Channel Prior ◽  
Single Image ◽  
Improved Method ◽  
Image Dehazing ◽  
Dark Channel ◽  
Single Image Dehazing

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

scholarly journals The Improved Algorithm of Fast Panorama Stitching for Image Sequence and Reducing the Distortion Errors

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Zhong Qu ◽  
Si-Peng Lin ◽  
Fang-Rong Ju ◽  
Ling Liu
Keyword(s):  
Feature Detection ◽  
Image Sequence ◽  
Input Image ◽  
Coordinate Space ◽  
Reference Image ◽  
Image Stitching ◽  
Feature Points ◽  
Improved Method ◽  
Sift Feature ◽  
Improved Algorithm

The traditional image stitching result based on the SIFT feature points extraction, to a certain extent, has distortion errors. The panorama, especially, would get more seriously distorted when compositing a panoramic result using a long image sequence. To achieve the goal of creating a high-quality panorama, the improved algorithm is proposed in this paper, including altering the way of selecting the reference image and putting forward a method that can compute the transformation matrix for any image of the sequence to align with the reference image in the same coordinate space. Additionally, the improved stitching method dynamically selects the next input image based on the number of SIFT matching points. Compared with the traditional stitching process, the improved method increases the number of matching feature points and reduces SIFT feature detection area of the reference image. The experimental results show that the improved method can not only accelerate the efficiency of image stitching processing, but also reduce the panoramic distortion errors, and finally we can obtain a pleasing panoramic result.

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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