Transform Domain Rain Removal Methods using
Dictionary Learning Approach: A Comparative Study
Journal:
GRENZE International Journal of Engineering and Technology
Authors:
Tangalla Manoj Kumar, M.V.N. Sai Maanas, Deep Gupta
Volume:
6
Issue:
2
Grenze ID:
01.GIJET.6.2.512
Pages:
310-315
Abstract
Rain removal from color images and videos is one of the challenging tasks in
image processing. This paper proposes an efficient algorithm for the removal of rain from
rainy images. This paper shows the comparison of different techniques that can be adopted
to remove rain from color images. While several previous pieces of the research proposed
different ways of obtaining a rain-free image by using a bilateral filter, guided filters along
with the dictionary learning method, this paper proposes a different approach i.e., using
hybrid l1-l0 decomposition for the separation of the image into low-frequency and highfrequency
components. The non-rain image details are extracted from the high-frequency
part based on the histogram of oriented gradient (HOG) features using dictionary learning.
These non-rain details are then added to the low-frequency part to obtain the final rain-free
image. This paper also shows the performance comparison of the proposed algorithm in the
presence of different filters for obtaining low and high-frequency components.