Image defogging enhancement method and system for fully mechanized coal mining face in dust fog environment

By using the combination of encoder and decoder in the image defogging technology, and using the DM module to couple features in the spatial and frequency domain, the shortcomings of the existing technology in dealing with complex blurred images and dense haze areas are solved, and more efficient image defogging and detail recovery are achieved, and the generalization ability of the model is improved.

CN119671904AActive Publication Date: 2025-03-21CHINA UNIV OF MINING & TECH
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Patent Information

Application Number
CN202411737422.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-11-29
Publication Date
2025-03-21
Estimated Expiration
2044-11-29

AI Technical Summary

Technical Problem

When using complex blurred images and dense haze areas, existing image defog removal technology is difficult to accurately capture haze distribution and reconstruct clear texture details, and mainly focuses on spatial domain feature extraction, with poor results.

Method used

A method of image defog enhancement in dust-fog environment of coal mine comprehensive mining working face is adopted. Through the combination of encoder and decoder, DM modules (including deformable convolution, DCM module, APGM module and SRU module) are used to couple spatial and frequency domain features in the spatial and frequency domain to integrate spatial and frequency domain information to improve the generalization ability of the model.

Benefits of technology

It improves the clarity of image feature extraction, restores the details and structure of the image, improves the defog removal effect and generalization capabilities of the model, and ensures the safe mining of coal mines.

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Abstract

The invention discloses an image defogging enhancement method and system for a fully mechanized coal mining face in a dust fog environment, and the method comprises the steps: obtaining a to-be-processed foggy image, carrying out the encoding operation of the foggy image through an encoder, and obtaining an encoding feature from the foggy image; inputting the obtained coding features into a bottleneck layer integrated by a DM module to realize feature coupling of the coding features in a space domain and a frequency domain to obtain fusion features; and carrying out decoding processing on the obtained fusion features through a decoder, and outputting to obtain a target defogged image. The system comprises a camera and an image defogging network model module based on double-domain coupling. The non-uniform haze feature representation and global feature perception are enhanced through the deformable convolution and amplitude phase guidance strategy, the image feature extraction definition of the model is improved, the details and structure of the image are restored, and the defogging effect and generalization and generalization ability of the model are improved.
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