Drop-size analysis using 2D Double Density Dual Tree Discrete Wavelet Transform

DOI

10.2991/iccasp-16.2017.62How to use a DOI?

Keywords

Raindrop analysis,DWT, image processing,double density dual tree transform, threshold Iterative segmentation

Abstract

This paper proposes a method for raindrop measurement based on image processing using 2D double density dual tree DWT.Concept which make this project is to use a technique apart from disdrometer to abstract parameter values such as drop size from image.Trasform technique 2D double density dual tree DWT which is also know as framelet transform is four time as expansive compared to simple discrete signal.In Propsed method images are captured through experimental setup using two cameras with advanced features, in such a way that both captured images have same central point. Captured images are decomposed into two low frequency components and sixteen high frequency components using 2D double density dual tree transform. These components are fused together employing maximum selection fusion technique. Inverse transform is applied and then Iterative segmentation is carried out on fused image to get results in the form of relative bias, maximum drop size, minimum drop size, number of raindrops in a given image.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - S. Tawade
AU  - P. Ghonge
AU  - K. Tuckley
PY  - 2016/12
DA  - 2016/12
TI  - Drop-size analysis using 2D Double Density Dual Tree Discrete Wavelet Transform
BT  - Proceedings of the International Conference on Communication and Signal Processing 2016 (ICCASP 2016)
PB  - Atlantis Press
SP  - 411
EP  - 418
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasp-16.2017.62
DO  - 10.2991/iccasp-16.2017.62
ID  - Tawade2016/12
ER  -