Restoration of Single Sand-Dust Image Based on Style Transformation and Unsupervised Adversarial Learning

Restoration of Single Sand-Dust Image Based on Style Transformation and Unsupervised Adversarial Learning

Since dust particles in the air scatter and absorb light, images captured in sand-dust weather mostly show low contrast, color deviation and blurriness, seriously affecting the reliability of visual tasks. Currently, pixel-level enhancement and prior-based methods are used to restore sand-dust image...

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Bibliographic Details
Main Authors: Bosheng Ding, Huimin Chen, Lixin Xu, Ruiheng Zhang
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Style transformation
unsupervised adversarial learning
sand-dust image restoration
Online Access:https://ieeexplore.ieee.org/document/9862990/

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