摘要
由于气候变化、空气污染等原因,含雾图像的产生不可避免。对含雾图像进行去雾处理是消除雾对图像的不良影响,进而获得细节纹理等方面高质量的清晰图像。首先,主要就图像增强、物理模型和深度学习三个方面对图像去雾算法的研究现状进行系统的归纳总结,包括各类去雾算法的优缺点分析。其次,指出去雾算法的问题所在。最后,提出去雾算法的前景展望。
Due to climate change,air pollution and other reasons,fog-containing images are inevitable. Defogging the fog-containing image is to eliminate the bad influence of fog on the image,and then obtain high-quality and clear images in detail and texture. Firstly,the research status of image defogging algorithms is systematically summarized from three aspects:image enhancement,physical model and deep learning,including the advantages and disadvantages of various defogging algorithms. Secondly,the problems of defogging algorithm are pointed out. Finally,the prospect of defogging algorithm is proposed.
作者
谢勇
贾惠珍
王同罕
雷初聪
徐铠珈
陈青
XIE Yong;JIA Huizhen;WANG Tonghan;LEI Chucong;XU Kaijia;CHEN Qing(Jiangxi Radioactive Geoscience Large Data Technology Engineering Laboratory,East China University of Technology,Nanchang 330013;Institute of Computer Science and Technology,Ningbo University,Ningbo 315211;Institute of Artificial Intelligence,Nanchang Institute of Science&Technology,Nanchang 330108)
出处
《计算机与数字工程》
2022年第12期2765-2774,共10页
Computer & Digital Engineering
基金
国家重点研发计划(编号:2018YFB1702700)
江西省核地学数据科学与系统工程技术研究中心开放基金项目(编号:JETRCNGDSS201901)
江西省教育厅科技项目(编号:GJJ190364)资助。
关键词
去雾
图像增强
物理模型
深度学习
defogging
image enhancement
physical model
deep learning