Computer vision for the remote sensing of atmospheric visibility

Babari, Raouf; Hautiére, Nicolas; Dumont, Éric; Papelard, Jean-Pierre; Paparoditis, Nicolas

doi:10.1109/iccvw.2011.6130246

Cited by 15 publications

(10 citation statements)

References 16 publications

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“…However, these basic filters are sensitive to illumination variations. To solve this problem, Babari et al [13] used the estimate of the Lambertianess of the image pixels as a weight for the estimated image contrast. Yang [8] proposed an algorithm with the Haar function to improve non-uniform illumination sharpness.…”

Section: Introductionmentioning

confidence: 99%

Single Image-Based Scene Visibility Estimation

Xie

2019

IEEE Access

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This paper proposes a novel method to utilize a single daylight image of the observed scene to estimate the extinction coefficient of the observed atmosphere and obtain the scene visibility. The proposed method consists of three steps. First, based on the theory of atmospheric physics, we estimate the extinction coefficient of the clear atmosphere in an observed scene. Second, a method combining the dark channel prior and the edge collapse-based transmission refinement is employed to calculate the ratio between the extinction coefficient of the observed atmosphere and that of the clear atmosphere. This ratio indicates the increased degree of the extinction coefficient due to the increment of the atmospheric turbidity. Finally, by multiplying the extinction coefficient of the clear atmosphere and the ratio, the extinction coefficient of the observed atmosphere is calculated and the scene visibility is obtained. The numerous experiments on the proposed method suggest that it performs well in measuring the scene visibility in various types of scenes without additional assistance (e.g., geometric calibration of the camera, road marking extraction, and ground truth data collection).

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Section: Introductionmentioning

confidence: 99%

Single Image-Based Scene Visibility Estimation

Xie

2019

IEEE Access

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“…Most definitely, by measuring the scattered light or by extinction coefficient analysis the atmospheric visibility may be assessed [1][2]. The devices described as transmissiometers or scatterometers utilize optical sensors to determine atmospheric visibility and visual range characteristic.…”

Section: Introductionmentioning

confidence: 99%

“…In the latter case of measuring devices, called scatterometers, the operational routine of those is based upon the measurement of the light beam being scattered within the aerosol environment in a narrow optical volume. Scatterometers evaluate the light beam dispersion, however the reliability of such measurement outcome is of dubious nature [2][3][4]. Yet another branch of devices utilized for measurement of atmospheric visibility is based on the backscattering phenomenon [5][6][7].…”

Section: Introductionmentioning

confidence: 99%

New atmospheric visibility optical sensor based on correlation coding method

2014

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In this article a new atmospheric visibility sensor design is presented. It employs an empirical link between acquired lidar backscattered signals and atmospheric visibility parameter. In particular, received backscattered beam is under the autocorrelation analysis within the defined correlation distance, thus the outcome of this procedure presents the overall characteristic of the correlation coefficients, as a function of examined space range. Specifically, significant points of interest of this characteristic are then extracted and processed in order to evaluate the atmospheric visibility parameter. In various experimental demo campaigns, under varying weather conditions, performance of the designed device was assessed. It is reported, the approximate range of reliable atmospheric visibility parameter evaluation falls into the interval of 100 to 1400 m.

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“…In this method, features related to the extinction coefficient or visibility distance are extracted from the image to evaluate the visibility based on the meteorological law. For example, Babari et al [7]- [9] proposed a physics-based model to express the mapping between the contrast and the atmospheric visibility distance with the consideration of Lambertian surfaces of the scene. Carretas et al [10] used two tree sets located at different but known distances to calculate the extinction coefficient based on the different wavelengths associated with R,G,B channels of the image to get the visibility.…”

Section: Introductionmentioning

confidence: 99%

Meteorological Visibility Evaluation on Webcam Weather Image Using Deep Learning Features

Hong¹,

Lo²

2017

IJCTE

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Abstract-The estimation methods of meteorological visibility currently in use on digital image are mainly based on the meteorological laws and the corresponding features are extracted manually to calculate the visibility. However, besides the parameters of camera setting, the environmental and weather conditions will also affect the image quality and cause different kinds of noise to influence the evaluation accuracy. It is hard to extract all these factors manually and involve them into a certain equation to solve the visibility. Therefore, it is necessary to intelligently extract the useful factors and evaluate visibility. In this paper, an intelligent digital method is proposed to estimate the visibility on webcam weather image. In this method, a pre-trained convolutional neural network (CNN) is employed to automatically extract the visibility features instead of manual method and a generalized regression neural network (GRNN) is designed for intelligent visibility evaluation based on these deep learning features. A series of weather photo with the ground truth of visibility is used to train and test the proposed method. The result shows that the proposed automatic method with deep learning feature is workable for visibility prediction, whose accuracy is higher than that of the traditional method with hand-crafted features.

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Computer vision for the remote sensing of atmospheric visibility

Abstract: Abstract

Cited by 15 publications

References 16 publications

Single Image-Based Scene Visibility Estimation

Single Image-Based Scene Visibility Estimation

New atmospheric visibility optical sensor based on correlation coding method

Meteorological Visibility Evaluation on Webcam Weather Image Using Deep Learning Features

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