Single image dehazing algorithm based on optical diffraction deep neural networks

Author:

Song Mingzhu1,Li Runze1,Guo Rong1,Ding Gege1ORCID,Wang Yuezhu1,Wang Junsheng1ORCID

Affiliation:

1. Dalian Maritime University

Abstract

Single image dehazing is a challenging task because of the hue and brightness distortion problems due to the atmospheric scattering. These problems limit the perceptual fidelity, as well as information integrity, of a given image. In this paper, we propose an image dehazing method based on the optical neural networks dehazing by simulating optical diffraction. The algorithm is trained from a large number of hazy images and their corresponding clean images. The experimental results demonstrate that the proposed method has reached an advanced level in both PSNR and SSIM dehazing performance indicators, and the amount of calculation is less than most artificial neural networks.

Funder

National Natural Science Foundation of China

Dalian high level Talents Innovation Support Plan

Dalian key field innovation team

Liaoning Province "Unveiling the list and Taking the lead" project

Fundamental Research Funds for the Central Universities

Publisher

Optica Publishing Group

Subject

Atomic and Molecular Physics, and Optics

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