NDLI: Characterising and predicting the movement of clouds using fractional-order optical flow

Content Provider	IET Digital Library
Author	Shakya, Snehlata Kumar, Sanjeev
Abstract	Estimating cloud motion with complex background through the sequence of satellite images plays an important role in weather forecasting. This motion can be used for characterization of clouds and predicting storms. Optical flow is used here for motion estimation which gives horizontal and vertical velocity components. Velocity field vector alone is not sufficient to analyze the cloud behavior for predicting extreme weather conditions and there is a need to develop some visual features for enhancing the weather prediction strategies. In this paper, we utilize the optical flow to localize the high alert regions. To have a better localization and motion signatures, we develop a fractional order technique to compute optical flow. Also, the localization is characterized by brightness of image, magnitude, directions, vorticity and irrotational components of the optical flow. We did analysis on sequence of images for Mumbai, India heavy rain that happened during August 28–29, 2017, cyclonic data sets for May 16, 2018, September 19–20, 2018 and October 14, 2018. Visual features show different patterns for extreme and normal weather situations. A study on interpolation and extrapolation of the image sequence is also presented. Optical flow based interpolation and Advection-anisotropic-diffusion based extrapolation model give promising results.
Starting Page	1375
Ending Page	1381
Page Count	7
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 8, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6100
Journal	IET Image Processing
Publisher Date	2019-04-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Atmospheric Temperature Cloud Motion Cloud Physics Clouds Computer Vision And Image Processing Technique Extreme Weather Condition Extreme Weather Situations Fractional Order Technique Fractional-order Optical Flow Image Sequence Instrumentation And Technique For Geophysical, Hydrospheric And Lower Atmosphere Research Interpolation Irrotational Component Localisation Meteorology Motion Estimation Motion Signatures Normal Weather Situations Optical, Image And Video Signal Processing Optical-flow-based Interpolation Predicting Storms Rain Satellite Image Storms Velocity Field Vector Vertical Velocity Component Visual Feature Vorticity Weather Analysis And Prediction Weather Forecasting Weather Prediction Strategy
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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