Denoising of image using bilateral filtering in multiresolution

Abstract

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.