MAP-MRF Estimation Based Weather Radar Visualization
Summary :
Real-time weather radar imaging technology is required for generating short-time weather forecasts. Moreover, such technology plays an important role in critical-weather warning systems that are based on vast Doppler weather radar data. In this study, we propose a weather radar imaging method that uses multi-layer contour detection and segmentation based on MAP-MRF estimation. The proposed method consists of three major steps. The first step involves generating reflectivity and velocity data using the Doppler radar in the form of raw data images of sweep unit in the polar coordinate system. Then, contour lines are detected on multi-layers using the adaptive median filter and modified Canny's detector based on curvature consistency. The second step interpolates contours on the Cartesian coordinate system using 3D scattered data interpolation and then segments the contours based on MAP-MRF prediction and the metropolis algorithm for each layer. The final step involves integrating the segmented contour layers and generating PPI images in sweep units. Experimental results show that the proposed method produces a visually improved PPI image in 45% of the time as compared to that for conventional methods.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.7 pp.1924-1932
- Publication Date
- 2018/07/01
- Publicized
- 2018/04/10
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017EDP7212
- Type of Manuscript
- PAPER
- Category
- Image Processing and Video Processing
Authors
Suk-Hwan LEE
Tongmyong University
Keyword
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Suk-Hwan LEE, "MAP-MRF Estimation Based Weather Radar Visualization" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 7, pp. 1924-1932, July 2018, doi: 10.1587/transinf.2017EDP7212.
Abstract: Real-time weather radar imaging technology is required for generating short-time weather forecasts. Moreover, such technology plays an important role in critical-weather warning systems that are based on vast Doppler weather radar data. In this study, we propose a weather radar imaging method that uses multi-layer contour detection and segmentation based on MAP-MRF estimation. The proposed method consists of three major steps. The first step involves generating reflectivity and velocity data using the Doppler radar in the form of raw data images of sweep unit in the polar coordinate system. Then, contour lines are detected on multi-layers using the adaptive median filter and modified Canny's detector based on curvature consistency. The second step interpolates contours on the Cartesian coordinate system using 3D scattered data interpolation and then segments the contours based on MAP-MRF prediction and the metropolis algorithm for each layer. The final step involves integrating the segmented contour layers and generating PPI images in sweep units. Experimental results show that the proposed method produces a visually improved PPI image in 45% of the time as compared to that for conventional methods.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017EDP7212/_p
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@ARTICLE{e101-d_7_1924,
author={Suk-Hwan LEE, },
journal={IEICE TRANSACTIONS on Information},
title={MAP-MRF Estimation Based Weather Radar Visualization},
year={2018},
volume={E101-D},
number={7},
pages={1924-1932},
abstract={Real-time weather radar imaging technology is required for generating short-time weather forecasts. Moreover, such technology plays an important role in critical-weather warning systems that are based on vast Doppler weather radar data. In this study, we propose a weather radar imaging method that uses multi-layer contour detection and segmentation based on MAP-MRF estimation. The proposed method consists of three major steps. The first step involves generating reflectivity and velocity data using the Doppler radar in the form of raw data images of sweep unit in the polar coordinate system. Then, contour lines are detected on multi-layers using the adaptive median filter and modified Canny's detector based on curvature consistency. The second step interpolates contours on the Cartesian coordinate system using 3D scattered data interpolation and then segments the contours based on MAP-MRF prediction and the metropolis algorithm for each layer. The final step involves integrating the segmented contour layers and generating PPI images in sweep units. Experimental results show that the proposed method produces a visually improved PPI image in 45% of the time as compared to that for conventional methods.},
keywords={},
doi={10.1587/transinf.2017EDP7212},
ISSN={1745-1361},
month={July},}
Copy
TY - JOUR
TI - MAP-MRF Estimation Based Weather Radar Visualization
T2 - IEICE TRANSACTIONS on Information
SP - 1924
EP - 1932
AU - Suk-Hwan LEE
PY - 2018
DO - 10.1587/transinf.2017EDP7212
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2018
AB - Real-time weather radar imaging technology is required for generating short-time weather forecasts. Moreover, such technology plays an important role in critical-weather warning systems that are based on vast Doppler weather radar data. In this study, we propose a weather radar imaging method that uses multi-layer contour detection and segmentation based on MAP-MRF estimation. The proposed method consists of three major steps. The first step involves generating reflectivity and velocity data using the Doppler radar in the form of raw data images of sweep unit in the polar coordinate system. Then, contour lines are detected on multi-layers using the adaptive median filter and modified Canny's detector based on curvature consistency. The second step interpolates contours on the Cartesian coordinate system using 3D scattered data interpolation and then segments the contours based on MAP-MRF prediction and the metropolis algorithm for each layer. The final step involves integrating the segmented contour layers and generating PPI images in sweep units. Experimental results show that the proposed method produces a visually improved PPI image in 45% of the time as compared to that for conventional methods.
ER -
English
