Adaptive linear transmission estimation dehazing algorithm

YANG Yan; LI Yifei; YUE Hui

doi:10.5768/JAO201940.0302007

Volume 40 Issue 3

May 2019

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YANG Yan, LI Yifei, YUE Hui. Adaptive linear transmission estimation dehazing algorithm[J]. Journal of Applied Optics, 2019, 40(3): 447-453. doi: 10.5768/JAO201940.0302007

Citation:

YANG Yan, LI Yifei, YUE Hui. Adaptive linear transmission estimation dehazing algorithm[J]. Journal of Applied Optics, 2019, 40(3): 447-453. doi: 10.5768/JAO201940.0302007

YANG Yan, LI Yifei, YUE Hui. Adaptive linear transmission estimation dehazing algorithm[J]. Journal of Applied Optics, 2019, 40(3): 447-453. doi: 10.5768/JAO201940.0302007

Citation:

YANG Yan, LI Yifei, YUE Hui. Adaptive linear transmission estimation dehazing algorithm[J]. Journal of Applied Optics, 2019, 40(3): 447-453. doi: 10.5768/JAO201940.0302007

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Adaptive linear transmission estimation dehazing algorithm

doi: 10.5768/JAO201940.0302007

College of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China

Received Date: 2018-11-16
Rev Recd Date: 2018-12-17
Publish Date: 2019-05-01

Abstract

Abstract

In order to effectively restore the degraded images in hazy weather, an adaptive linear transmission estimation dehazing algorithm was proposed. Firstly, we created a linear transformation model between the hazy image and the dehazing image minimum channel. Secondly, the adaptive parameters were obtained by using the mixed channel of the hazy image, and the transmission was estimated by combining the adaptive parameter and the linear transformation model. Then, a Gaussian function was constructed by the minimum channel of the hazy image to compensate the estimated transmission of the bright region, and the accuracy of the transmission of this region was improved, and the cross-bilateral filter was used to eliminate the texture effect to obtain the optimized transmission. Finally, a dehazing image was restored in combination with the atmospheric scattering model. The experimental results show that the method can effectively reduce the time complexity, and the restored image has obvious details and appropriate brightness.
- dehazing,
- adaptive linear transformation,
- Gaussian function,
- atmospheric scattering model

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References(15)

References

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