Open AccessDenoising of image using bilateral filtering in multiresolution
Author(s) -
Alaa Abid Muslam Abid Ali,
Mohammed Iqbal Dohan,
Saif Khalid Musluh
Publication year - 2020
Publication title -
aptikom journal on computer science and information technologies
Language(s) - English
Resource type - Journals
eISSN - 2528-2425
pISSN - 2528-2417
DOI - 10.34306/csit.v3i1.76
Subject(s) - bilateral filter , smoothing , wavelet , noise reduction , transformation (genetics) , filter (signal processing) , non local means , artificial intelligence , noise (video) , image (mathematics) , enhanced data rates for gsm evolution , multiresolution analysis , computer science , image processing , filter bank , computer vision , edge preserving smoothing , mathematics , algorithm , wavelet transform , image denoising , wavelet packet decomposition , biochemistry , chemistry , gene
One of the very efficient and resource conservative image processing methodology is with the help of bilateral filters. This technique filters the image without the help of edge smoothing but it does employs spatial averaging in a non-linear way. The filtering technique discussed above is very much dependent on the parameters of its filters. A very slight change in filter parameter values effects the outputs and results in a most drastic manner. In this paper, the author has worked on two contributions. In the applications concerning image denoising, the author has contributed in study of the parameter selection of bilateral filters which are optimal in nature. The contribution number two is about extending the present work i.e. extension of the filters which are bilateral in nature. In this process, the bilateral filtering of images is applied to the lower frequency sub-bands which is also known as approximation sub-band. This sub-band is obtained by using the wavelet transformations. Hence, a new framework for image denoising will be created which will be combination of multiresolution bilateral filtering and wavelets transformation techniques. As a matter of fact, this combination is efficient in contradicting noise from an image.