@inproceedings{a22de33d2b0e463ea7b3e54e81bcadcb,
title = "On the improvement of volterra equation based filtering for image denoising",
abstract = "This paper presents a simple but effective approach for the removal of additive white Gaussian noise from digital images. In our approach, a generalization of a linear heat equation, obtained by replacing time derivative to a fractional time derivative of order between 1 and 2 has been used and a pixel by pixel technique applied. The choice of order of fractional time derivative has been made for each pixel by using structure tensor of image, which allows us to control the diffusion process without introducing nonlinearities in equation as in classical approaches. The proposed model is well posed and numerical scheme adopted is stable. Several experiments showing improvement of our approach visually and in terms of SNR, PSNR are also provided.",
keywords = "Convolution quadrature methods, Fractional integrals and derivatives, Structure tensor, Volterra equations",
author = "Eduardo Cuesta and Mokhtar Kirane and Malik, {Salman A.}",
year = "2011",
language = "British English",
isbn = "9781601321916",
series = "Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011",
pages = "733--738",
booktitle = "Proceedings of the 2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011",
note = "2011 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2011 ; Conference date: 18-07-2011 Through 21-07-2011",
}