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Rain and snow removal using multi-guided filter and anisotropic gradient in the quaternion framework
Author(s): V. Voronin; E. Semenishchev; M. Zhdanova; R. Sizyakin; A. Zelenskii
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Paper Abstract

In many cases the rain and snow on an image significantly degrade the effectiveness of any computer vision algorithm, such as object recognition, tracking, retrieving and so on. The automated detection and removing such degradations in a color image is still a challenging task. This paper presents a new rain and snow removal method using low- and highfrequency parts of a single image. For this purpose, we use a color image multi-guided filter and anisotropic gradient in Hamiltonian quaternions. The quaternion framework is used to represent a color image to take into account all three channels simultaneously when inpainting the RGB image. Our results show that it has good performance in rain removal and snow removal.

Paper Details

Date Published: 24 September 2019
PDF: 7 pages
Proc. SPIE 11169, Artificial Intelligence and Machine Learning in Defense Applications, 111690S (24 September 2019); doi: 10.1117/12.2534744
Show Author Affiliations
V. Voronin, Don State Technical Univ. (Russian Federation)
Moscow State Univ. of Technology (Russian Federation)
E. Semenishchev, Don State Technical Univ. (Russian Federation)
Moscow State Univ. of Technology (Russian Federation)
M. Zhdanova, Moscow State Univ. of Technology (Russian Federation)
R. Sizyakin, Don State Technical Univ. (Russian Federation)
A. Zelenskii, Moscow State Univ. of Technology (Russian Federation)


Published in SPIE Proceedings Vol. 11169:
Artificial Intelligence and Machine Learning in Defense Applications
Judith Dijk, Editor(s)

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