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Single image dehazing algorithm based on optical diffraction deep neural networks
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DOI：10.1364/OE.458610.png)
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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. (C) 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
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IF:
3.3
论文数:
6.1W
被引数:
14.3W
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分享收藏Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification.png)
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