Adaptive Dehaze Method for Aerial Image Processing

被引:0
|
作者
Xu, Rong-qin [1 ]
Zhong, Sheng-hua [1 ]
Tang, Gaoyang [1 ]
Wu, Jiaxin [1 ]
Zhu, Yingying [1 ]
机构
[1] Shenzhen Univ, Coll Comp Sci & Software Engn, Shenzhen, Peoples R China
来源
IMAGE AND VIDEO TECHNOLOGY (PSIVT 2017) | 2018年 / 10749卷
基金
中国国家自然科学基金;
关键词
Adaptive haze removal; SIFT detector and descriptor; Image matching; Image stitching; Kernel graph cuts; Random walk;
D O I
10.1007/978-3-319-75786-5_24
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Remote sensing images or images collected by unmanned aerial vehicles in the hazy weather are easily interfered by scattering effect generated by atmospheric particulate matter. The terrible interference will not only lead to the images quality seriously degraded, but also result in a bad effect on the process of images feature extraction and images feature matching. In this paper, by proposing an effective adaptive dehaze method, we compare the statistical results of feature detection and matching based on Scale-invariant feature transform (SIFT) detector and descriptor before and after haze removal. And we also provide the comparisons of image stitching task. The experimental results show that, after the haze removal is implemented on hazy images, more SIFT feature keypoints and SIFT matching keypoints will be extracted, which is also beneficial to images stitching. Moreover, the proposed adaptive method performs better than the original dehaze method.
引用
收藏
页码:290 / 301
页数:12
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