Real-time endoscopy haze removal: a synthetical method

被引：0
|
作者：
Xu Zhuo
Chenbin Yang
Yuming Gao
Zhihua Wang
Yang Chen
Ke Wu
机构：
[1] Southeast University,Laboratory of Image Science and Technology, School of Computer Science and Engineering
[2] Tuge Medical Technology Co.,School of Computer Science and Engineering
[3] Ltd.,Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University)
[4] Southeast University,undefined
[5] Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing,undefined
[6] Ministry of Education,undefined
来源：
Multimedia Tools and Applications | 2024年 / 83卷
关键词：
Video dehazing; Endoscopy haze removal; Refined Dark Channel prior; Markov random field; Color attenuation prior;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In endoscopic surgeries, the smoke and haze generated by temperature difference and electrosurgical knife usage degrades the surgical view. While many researches on natural single image haze removal being proposed, few works are done for video haze removal of endoscopy view. In this paper, we proposed a synthetical method for endoscopy haze removal combining a Refined Dark Channel Prior (RDCP), Spatial-Temporal Markov Random Field (STMRF), Color Attenuation Prior (CAP) and parameter self-adaption. Qualitative and quantitative experiment results outperformed some traditional and deep learning based methods. Our proposed method is an effective and practical one.
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收藏
页码：31195 / 31209
页数：14
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