Rain and snow removal using multi-guided filter and anisotropic gradient in the quaternion framework
Viacheslav Voronin, Evgeny A. Semenishchev, Marina M. Zhdanova, Roman Sizyakin, Alexander Zelenskii · 2019
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.