Single image defogging method and device based on image prior and global block aggregation

Through the method of image prior and global block aggregation, combined with the non-local defog removal module and the local feature enhancement module, the problem of poor fog removal effect in the existing technology is solved, and efficient fog removal and real image recovery in complex fog scenes are achieved.

CN116402697BActive Publication Date: 2025-08-22SOUTH CHINA AGRICULTURAL UNIVERSITY
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Patent Information

Application Number
CN202310042779.2
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-01-28
Publication Date
2025-08-22
Estimated Expiration
2043-01-28

AI Technical Summary

Technical Problem

The existing image defog removal method has poor effect on complex fog scenes, which is prone to visual artifacts, lacks consideration of local and global information complementarity, and has high calculation consumption.

Method used

Using the method based on image prior and global block aggregation, a clear feature is found in the global scope through the non-local defog module, and the adversarial learning of the local feature enhancement module and dark channel prior is optimized to improve the defog effect.

Benefits of technology

Improve fog removal performance in complex fog scenes, reduce visual artifacts, and truly restore image color and texture details, improving image authenticity.

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Abstract

The present invention discloses a single image defogging method and device based on image prior and global block aggregation. The method includes: using multiple pre-established feature defoggers to convert a foggy image into enhanced defogging features at multiple scales; a feature defogger includes two parallel branches, in branch one, global clear features are aggregated according to image self-similarity to obtain a global defogging feature; in branch two, feature extraction provides more local features for the global defogging feature; the features output by the two branches are fused to obtain an enhanced defogging feature at one scale, and the global defogging feature and the local detail feature are added element by element during the fusion process; finally, the enhanced defogging features at multiple scales are input into a fog-free image decoder to recover a clear image after defogging. The present invention can effectively improve the defogging performance in complex scenes. In particular, while reducing the generation of visual artifacts, the image details are more accurately restored to generate a more realistic clear image.
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