scholarly journals An Automated Cirrus Cloud Detection Method for a Ground-Based Cloud Image

2012 ◽  
Vol 29 (4) ◽  
pp. 527-537 ◽  
Author(s):  
Jun Yang ◽  
Weitao Lu ◽  
Ying Ma ◽  
Wen Yao
Keyword(s):  
Background Subtraction ◽  
Estimation Method ◽  
Basic Research ◽  
Adaptive Threshold ◽  
Cirrus Clouds ◽  
Detection Methods ◽  
Cirrus Cloud ◽  
Cloud Detection ◽  
Threshold Method ◽  
Blue Band

Abstract Cloud detection is a basic research for achieving cloud-cover state and other cloud characteristics. Because of the influence of sunlight, the brightness of sky background on the ground-based cloud image is usually nonuniform, which increases the difficulty for cirrus cloud detection, and few detection methods perform well for thin cirrus clouds. This paper presents an effective background estimation method to eliminate the influence of variable illumination conditions and proposes a background subtraction adaptive threshold method (BSAT) to detect cirrus clouds in visible images for the small field of view and mixed clear–cloud scenes. The BSAT algorithm consists of red-to-blue band operation, background subtraction, adaptive threshold selection, and binarization. The experimental results show that the BSAT algorithm is robust for all types of cirrus clouds, and the quantitative evaluation results demonstrate that the BSAT algorithm outperforms the fixed threshold (FT) and adaptive threshold (AT) methods in cirrus cloud detection.

scholarly journals An automated cloud detection method based on the green channel of total-sky visible images

2015 ◽  
Vol 8 (11) ◽  
pp. 4671-4679 ◽  
Author(s):  
J. Yang ◽  
Q. Min ◽  
W. Lu ◽  
W. Yao ◽  
Y. Ma ◽  
...  
Keyword(s):  
Detection Algorithm ◽  
Mie Scattering ◽  
Brightness Distribution ◽  
Adaptive Threshold ◽  
Cloud Detection ◽  
Blue Band ◽  
Green Channel ◽  
The Past ◽  
Visible Images ◽  
Cloud Mask

Abstract. Obtaining an accurate cloud-cover state is a challenging task. In the past, traditional two-dimensional red-to-blue band methods have been widely used for cloud detection in total-sky images. By analyzing the imaging principle of cameras, the green channel has been selected to replace the 2-D red-to-blue band for detecting cloud pixels from partly cloudy total-sky images in this study. The brightness distribution in a total-sky image is usually nonuniform, because of forward scattering and Mie scattering of aerosols, which results in increased detection errors in the circumsolar and near-horizon regions. This paper proposes an automatic cloud detection algorithm, "green channel background subtraction adaptive threshold" (GBSAT), which incorporates channel selection, background simulation, computation of solar mask and cloud mask, subtraction, an adaptive threshold, and binarization. Five experimental cases show that the GBSAT algorithm produces more accurate retrieval results for all these test total-sky images.

scholarly journals Retrieval algorithm for CO<sub>2</sub> and CH<sub>4</sub> column abundances from short-wavelength infrared spectral observations by the Greenhouse Gases Observing Satellite

2010 ◽  
Vol 3 (6) ◽  
pp. 4791-4833 ◽  
Author(s):  
Y. Yoshida ◽  
Y. Ota ◽  
N. Eguchi ◽  
N. Kikuchi ◽  
K. Nobuta ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gases ◽  
Short Wavelength ◽  
Near Infrared ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Detection Methods ◽  
Retrieval Algorithm ◽  
Random Errors ◽  
Cloud Detection

Abstract. The Greenhouse gases Observing SATellite (GOSAT) was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS). The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from the instrumental noise. The interferences by auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and the temporal variation patterns of the retrieved column abundances agree well with the current state of knowledge.

scholarly journals Cirrus cloud shape detection by tomographic extinction retrievals from infrared limb emission sounder measurements

2020 ◽  
Author(s):  
Jörn Ungermann ◽  
Irene Bartolome ◽  
Sabine Grießbach ◽  
Reinhold Spang ◽  
Christian Rolf ◽  
...  
Keyword(s):  
False Positive ◽  
Cirrus Clouds ◽  
Second Step ◽  
Small Scale ◽  
Cirrus Cloud ◽  
Spatial Accuracy ◽  
Cloud Detection ◽  
Index Method ◽  
Spatial Overlap ◽  
Imaging Instrument

Abstract. An improved cloud index-based method for the detection of clouds in limb sounder data is presented that exploits the spatial overlap of measurements to more precisely detect the location of (optically thin) clouds. A second method based on a tomographic extinction retrieval is also presented. Using CALIPSO data and a generic advanced infrared limb imaging instrument as example for a synthetic study, the new cloud index method is better in detecting the horizontal cloud extent in comparison to the traditional cloud index and has a reduction of false positive cloud detection events by about 30 %. The results for the extinction retrieval show even an improvement of 60 %. In a second step, the extinction retrieval is applied to real 3-D measurements of the air-borne limb sounder GLORIA taken during the Wave-driven ISentropic Exchange (WISE) campaign to retrieve small-scale cirrus clouds with high spatial accuracy.

ADAPTIVE THRESHOLD BACKGROUND SUBTRACTION FOR DETECTING MOVING OBJECT ON CONVEYOR BELT

2017 ◽  
Vol 5 (4) ◽  
pp. 46-51
Author(s):  
D.P. Tripathy ◽  
K. Guru Raghavendra Reddy
Keyword(s):  
Object Detection ◽  
Background Subtraction ◽  
Conveyor Belt ◽  
Adaptive Threshold ◽  
Object Identification ◽  
Moving Object Detection ◽  
Moving Object ◽  
Detection Methods ◽  
Accurate Identification ◽  
Frame Difference

Moving object detection is an important task in many computer vision classifications applications. The goal of this study is to identify a moving object detection method that provides a reliable and accurate identification of objects on the conveyor belt. In this paper, a study of the moving object detection methods is presented. Firstly, moving object detection pixel by pixel was performed using background subtraction, frame difference method. The threshold value in both background subtraction and frame difference is a fixed value, which determines the accuracy of object identification. The adaptive threshold values were calculated for both the methods to improve the accuracy. The performance of these methods was compared with the ground truth image.

scholarly journals An automated cloud detection method based on green channel of total sky visible images

2015 ◽  
Vol 8 (5) ◽  
pp. 4581-4605 ◽  
Author(s):  
J. Yang ◽  
Q. Min ◽  
W. Lu ◽  
W. Yao ◽  
Y. Ma ◽  
...  
Keyword(s):  
Detection Algorithm ◽  
Mie Scattering ◽  
Brightness Distribution ◽  
Adaptive Threshold ◽  
Cloud Detection ◽  
Visual Effects ◽  
Blue Band ◽  
Green Channel ◽  
Visible Images ◽  
Cloud Mask

Abstract. Getting an accurate cloud cover state is a challenging task. In the past, traditional two-dimensional red-to-blue band methods have been widely used for cloud detection in total sky images. By analyzing the imaging principle of cameras, green channel has been selected to replace the 2-D red-to-blue band for total sky cloud detection. The brightness distribution in a total sky image is usually non-uniform, because of forward scattering and Mie scattering of aerosols, which results in increased detection errors in the circumsolar and near-horizon regions. This paper proposes an automatic cloud detection algorithm, "green channel background subtraction adaptive threshold" (GBSAT), which incorporates channel selection, background simulation, computation of solar mask and cloud mask, subtraction, adaptive threshold, and binarization. Several experimental cases show that the GBSAT algorithm is robust for all types of test total sky images and has more complete and accurate retrievals of visual effects than those found through traditional methods.

scholarly journals Observation of Cirrus Clouds with GLORIA during the WISE Campaign: Detection Methods and Cirrus Characterization

2020 ◽  
Author(s):  
Irene Bartolome Garcia ◽  
Reinhold Spang ◽  
Jörn Ungermann ◽  
Sabine Griessbach ◽  
Martina Krämer ◽  
...  
Keyword(s):  
Reanalysis Data ◽  
Cirrus Clouds ◽  
Detection Sensitivity ◽  
Radiation Budget ◽  
Detection Methods ◽  
Climate Projections ◽  
Cloud Detection ◽  
Data Set ◽  
Research Aircraft

Abstract. Cirrus clouds contribute to the general radiation budget of the Earth, playing an important role in climate projections. Of special interest are optically thin cirrus clouds close to the tropopause due to the fact that their impact is not yet well understood. Measuring these clouds is challenging as both high spatial resolution as well as a very high detection sensitivity are needed. These criteria are fulfilled by the infrared limb sounder GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere). This study presents a characterization of observed cirrus clouds using the data obtained by GLORIA aboard the German research aircraft HALO during the WISE (Wave-driven ISentropic Exchange) campaign in September/October 2017. We developed an optimized cloud detection method and derived macro-physical characteristics of the detected cirrus clouds such as cloud top height, cloud top bottom height, vertical extent and cloud top position with respect to the tropopause. The fraction of cirrus clouds detected above the tropopause is in the order of 13 % to 27 %. In general, good agreement with the clouds predicted by the ERA5 reanalysis data-set is obtained. However, cloud occurrence is ≈ 50 % higher in the observations for the region close to and above the tropopause. Cloud bottom heights are also detected above the tropopause. However, considering the uncertainties, we cannot confirm the formation of unattached cirrus layers above the tropopause.

scholarly journals Cirrus cloud shape detection by tomographic extinction retrievals from infrared limb emission sounder measurements

2020 ◽  
Vol 13 (12) ◽  
pp. 7025-7045
Author(s):  
Jörn Ungermann ◽  
Irene Bartolome ◽  
Sabine Griessbach ◽  
Reinhold Spang ◽  
Christian Rolf ◽  
...  
Keyword(s):  
False Positive ◽  
Horizontal Resolution ◽  
Cirrus Clouds ◽  
Second Step ◽  
Small Scale ◽  
Cirrus Cloud ◽  
Spatial Accuracy ◽  
Cloud Detection ◽  
Index Method ◽  
Imaging Instrument

Abstract. An improved cloud-index-based method for the detection of clouds in limb sounder data is presented that exploits the spatial overlap of measurements to more precisely detect the location of (optically thin) clouds. A second method based on a tomographic extinction retrieval is also presented. Using CALIPSO data and a generic advanced infrared limb imaging instrument as examples for a synthetic study, the new cloud index method has a better horizontal resolution in comparison to the traditional cloud index and has a reduction of false positive cloud detection events by about 30 %. The results for the extinction retrieval even show an improvement of 60 %. In a second step, the extinction retrieval is applied to real 3-D measurements of the airborne Gimballed Limb Observer for Radiance Imaging in the Atmosphere (GLORIA) taken during the Wave-driven ISentropic Exchange (WISE) campaign to retrieve small-scale cirrus clouds with high spatial accuracy.

scholarly journals Observation of cirrus clouds with GLORIA during the WISE campaign: detection methods and cirrus characterization

2021 ◽  
Vol 14 (4) ◽  
pp. 3153-3168
Author(s):  
Irene Bartolome Garcia ◽  
Reinhold Spang ◽  
Jörn Ungermann ◽  
Sabine Griessbach ◽  
Martina Krämer ◽  
...  
Keyword(s):  
Cirrus Clouds ◽  
Detection Sensitivity ◽  
Radiation Budget ◽  
Detection Methods ◽  
Climate Projections ◽  
Cloud Detection ◽  
Reanalysis Dataset ◽  
Research Aircraft ◽  
Good Agreement

Abstract. Cirrus clouds contribute to the general radiation budget of the Earth and play an important role in climate projections. Of special interest are optically thin cirrus clouds close to the tropopause due to the fact that their impact is not yet well understood. Measuring these clouds is challenging as both high spatial resolution as well as a very high detection sensitivity are needed. These criteria are fulfilled by the infrared limb sounder GLORIA (Gimballed Limb Observer for Radiance Imaging of the Atmosphere). This study presents a characterization of observed cirrus clouds using the data obtained by GLORIA aboard the German research aircraft HALO during the WISE (Wave-driven ISentropic Exchange) campaign in September and October 2017. We developed an optimized cloud detection method based on the cloud index and the extinction coefficient retrieved at the microwindow 832.4–834.4 cm−1. We derived macro-physical characteristics of the detected cirrus clouds such as cloud top height, cloud bottom height, vertical extent and cloud top position with respect to the tropopause. The fraction of cirrus clouds detected above the tropopause is on the order of 13 % to 27 %. In general, good agreement with the clouds predicted by the ERA5 reanalysis dataset is obtained. However, cloud occurrence is ≈ 50 % higher in the observations for the region close to and above the tropopause. Cloud bottom heights are also detected above the tropopause. However, considering the uncertainties, we cannot confirm the formation of unattached cirrus layers above the tropopause.

scholarly journals Variability of cirrus cloud properties using a Polly<sup>XT</sup> Raman Lidar over high and tropical latitudes

2019 ◽  
Author(s):  
Kalliopi Artemis Voudouri ◽  
Elina Giannakaki ◽  
Mika Komppula ◽  
Dimitris Balis
Keyword(s):  
Optical Properties ◽  
Optical Depth ◽  
Middle Latitude ◽  
Detection Algorithm ◽  
Cirrus Clouds ◽  
Cirrus Cloud ◽  
Raman Lidar ◽  
Cloud Detection ◽  
Cloud Optical Depth ◽  
Lidar Ratio

Abstract. Measurements of cirrus clouds geometrical and optical properties, performed with a multi-wavelength PollyXT Raman Lidar, during the period 2008 to 2016 are analysed. The measurements were performed with the same instrument, during sequential periods, in three places at different latitudes, Gual Pahari (28.43° N, 77.15° E, 243 m a.s.l) in India, Elandsfontein (26.25° S, 29.43° E, 1745 m a.s.l) in South Africa and Kuopio (62.74° N, 27.54° E, 190 m a.s.l) in Finland. The lidar dataset has been processed by an automatic cirrus cloud detection algorithm. In the following, we present a statistical analysis of the lidar derived geometrical characteristics (cloud boundaries, geometrical thickness) and optical properties of cirrus clouds (cloud optical depth, lidar ratio, ice crystal depolarization ratio) measured in different latitudes that correspond to subtropical and subarctic regions as well as their seasonal variability. The effect of multiple-scattering from ice particles to the derived optical products is also considered and corrected in this study. Our results show that, over the subtropical stations, cirrus layers, which have a noticeable monthly variability, were observed between 7 to 13 km, with mid-cloud temperatures ranging from −60 °C to −21 °C and a mean thickness of 1295 ± 489 m and 1383 ± 735 m for Gual Pahari and Elandsfontein respectively. The corresponding overall mean cirrus optical depth at 355 nm is calculated to be 0.59 ± 0.39 and 0.40 ± 0.33, with lidar ratio values at 355 nm of 26 ± 12 sr and 25 ± 6 sr, respectively. A more extended dataset was acquired for the subarctic area of Kuopio Finland, between 2012 and 2016. The estimated average geometrical thickness of the cirrus clouds over Kuopio is 1200 ± 585 m and the temperature values vary from −71 °C to −21 °C, while the mean cirrus optical depth at 355 nm is 0.25 ± 0.2, with an estimated mean lidar ratio of 33 ± 7 sr, similar to the idar ratio values observed over middle latitude stations. The kind of information presented here can be rather useful in the cirrus parameterizations required as input to radiative transfer models, and can be a complementary tool to satellite products that cannot provide cloud vertical structure. In addition, a ground-based statistics of the cirrus properties could be useful in the validation and improvement of the corresponding derived products from satellite retrievals.

scholarly journals Retrieval algorithm for CO<sub>2</sub> and CH<sub>4</sub> column abundances from short-wavelength infrared spectral observations by the Greenhouse gases observing satellite

2011 ◽  
Vol 4 (4) ◽  
pp. 717-734 ◽  
Author(s):  
Y. Yoshida ◽  
Y. Ota ◽  
N. Eguchi ◽  
N. Kikuchi ◽  
K. Nobuta ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Greenhouse Gases ◽  
Short Wavelength ◽  
Near Infrared ◽  
Transport Model ◽  
Estimation Method ◽  
Detection Methods ◽  
Retrieval Algorithm ◽  
Random Errors ◽  
Cloud Detection

Abstract. The Greenhouse gases Observing SATellite (GOSAT) was launched on 23 January 2009 to monitor the global distributions of carbon dioxide and methane from space. It has operated continuously since then. Here, we describe a retrieval algorithm for column abundances of these gases from the short-wavelength infrared spectra obtained by the Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS). The algorithm consists of three steps. First, cloud-free observational scenes are selected by several cloud-detection methods. Then, column abundances of carbon dioxide and methane are retrieved based on the optimal estimation method. Finally, the retrieval quality is examined to exclude low-quality and/or aerosol-contaminated results. Most of the retrieval random errors come from instrumental noise. The interferences due to auxiliary parameters retrieved simultaneously with gas abundances are small. The evaluated precisions of the retrieved column abundances for single observations are less than 1% in most cases. The interhemispherical differences and temporal variation patterns of the retrieved column abundances show features similar to those of an atmospheric transport model.

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