Image Enhancement under Transformer Oil Based on Multi-Scale Weighted Retinex

QIANG Hu; ZHONG Yuzhong; DIAN Songyi

doi:10.11999/JEIT240645

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QIANG Hu, ZHONG Yuzhong, DIAN Songyi. Image Enhancement under Transformer Oil Based on Multi-Scale Weighted Retinex[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240645

Citation:

QIANG Hu, ZHONG Yuzhong, DIAN Songyi. Image Enhancement under Transformer Oil Based on Multi-Scale Weighted Retinex[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240645

QIANG Hu, ZHONG Yuzhong, DIAN Songyi. Image Enhancement under Transformer Oil Based on Multi-Scale Weighted Retinex[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240645

Citation:

QIANG Hu, ZHONG Yuzhong, DIAN Songyi. Image Enhancement under Transformer Oil Based on Multi-Scale Weighted Retinex[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240645

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Image Enhancement under Transformer Oil Based on Multi-Scale Weighted Retinex

doi: 10.11999/JEIT240645

1.
College of Electrical Engineering, Sichuan University, Chengdu 610065, China
2.
State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering, Sichuan University, Chengdu 610065, China

Funds: The National Natural Science Foundation of China (62203314)

Received Date: 2024-07-23
Rev Recd Date: 2024-11-08

Available Online: 2024-11-13

Abstract

Abstract

Objective: To address degradation issues such as color distortion, low brightness, and detail loss in images captured under transformer oil. Methods: This paper proposes a multi-scale weighted Retinex algorithm for image enhancement. First, to alleviate color distortion, a hybrid dynamic color channel compensation algorithm is proposed. This algorithm compensates dynamically based on the attenuation of each channel in the captured image. Next, a sharpening weight strategy is proposed to tackle detail loss. Finally, a pyramid multi-scale fusion strategy is used to combine different-scale Retinex reflection components with their corresponding weight maps, resulting in clearer images under transformer oil. Results and Discussion: (Fig.5), (Fig.6), (Fig.7), (Table 1) Conclusions: Experimental results demonstrate that the algorithm effectively addresses the complex degradation issues of images captured under transformer oil.
- Image enhancement under transformer oil,
- Retinex,
- Channel compensation,
- Multi-scale weighted

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References(26)

References

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