Overview and Comparison of Python Image Processing Tools with Gabor Functions

Abstract

With the invention and development of digital photography technology, the number of images obtained for various purposes has dramatically increased. So the need arose for
efficient methods of processing, transferring and storing them. It is obvious that the methods
of working with images should be scientifically grounded and reflect the peculiarities of human
visual perception. One of such methods is systems of Gabor functions, which are a basis in
the space L
2
(R). Their construction is based on the application of the wavelet theory and
multiresolution analysis presented in this article.
The next step after building the necessary mathematical model of images is its efficient and
convenient software implementation. Python is a great tool for doing this. The purpose of this
article is to provide an overview and comparison of libraries containing ready-made implementations of these functions, both as simple linear filters and as whole wavelet-bases.