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Motion estimation on meteorological infrared data using a total brightness invariance hypothesis
Affiliation:1. Department of Computer Science, Punjab Engineering College, Chandigarh 160012, India;2. Computer Vision and Pattern Recognition Lab, Indian Institute of Technology Ropar, Rupnagar 140001, India;3. Department of Electronics and Telecommunication, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431606, India;1. School of Mechatronic Engineering, Changchun University of Technology, Changchun 130012, PR China;2. School of Mechanical Engineering, Dalian University of Technology, DaLian 116023, PR China
Abstract:This work investigates a novel approach for cloud motion wind (CMW) estimation of Meteosat infrared images. It is motivated by the fact that variational techniques, such as those employed for computing the optical flow, are successfully applied to many computer vision applications but fail in this particular applicative context, mainly because optical flow techniques are adapted to rigid objects on visible data. The objective of this work is not to propose a full operational process for CMW estimation, but rather to improve optical flow techniques by applying constraints adapted to the specificity of meteorological infrared imagery.
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