一种特征自我保留的弱光图像增强方法.pdf

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RECEPTION & DISPLAY Tobacco Guangxi Industrial Co., Ltd., Nanning 530001, China
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Abstract:
Most existing image enhancement methods usually enhance the brightness channel as a whole, which usually leads
to problems such as excessive enhancement, loss of detail, and color distortion. To overcome these problems, a low-light image
enhancement method SFPGAN based on Generative Adversarial Network (GAN) and feature self-preservation was proposed. Firstly,
the authenticity of the generated image is evaluated from color, brightness and texture. Secondly, the loss of feature self preservation is
introduced to retain the features of the original image. Finally, an image training model with a certain amount of normal brightness and
overexposure is used to make the model more robust. A large number of experiments show that the proposed method is superior to other
methods in visual quality and objective indicators, and more suitable for real images.
Keywords:
generative adversarial network; low-light images; ima