人工智能
薄雾
计算机视觉
图像融合
尺度不变特征变换
色调
计算机科学
融合
极化(电化学)
像素
光学
散射
模式识别(心理学)
特征提取
图像(数学)
物理
哲学
物理化学
气象学
语言学
化学
作者
Linghao Shen,Mohamed Reda,Yongqiang Zhao
出处
期刊:Applied Optics
[The Optical Society]
日期:2021-03-30
卷期号:60 (13): 3699-3699
被引量:11
摘要
Atmospheric absorption and scattering (e.g., haze) cause degradation in the image quality of outdoor scenes, which affects the image-matching process. The scale-invariant feature transform (SIFT) algorithm is not effective in haze. Edge information is required to enhance the matching process. Utilizing the polarization information expressed by the Stokes vector component S1 with its edge information can improve the keypoint localization in the matching process. In this paper, a novel, to the best of our knowledge, fusion method called polarized intensity-hue-saturation is proposed that uses polarization and depth information by fusion of a polarized haze-removed image with the estimated depth and by applying S1. The instant dehazing method uses polarized images to obtain a haze-removed image and its estimated depth map. The fused image has high spatial details required for enhancing the matching process. The experimental results show that the proposed method outperforms the existing image-matching schemes and improves the conventional SIFT matching method.
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