Restoration of Noisy Multispectral Images with a Geodetic Distance Filter
- 作者: Karnaukhov V.1, Mozerov M.1
-
隶属关系:
- Kharkevich Institute for Information Transmission Problems
- 期: 卷 63, 编号 6 (2018)
- 页面: 612-615
- 栏目: Mathematical Models and Computational Methods
- URL: https://journals.rcsi.science/1064-2269/article/view/199874
- DOI: https://doi.org/10.1134/S1064226918060128
- ID: 199874
如何引用文章
详细
A number of algorithms for image filtering based on the geodetic distance kernel have been proposed recently. When applied to noisy images, some of them yield restoration results that are comparable to those provided by the best modern algorithms. An algorithm of this class that improves the restoration result for multispectral images is proposed. The algorithm uses a convolution kernel based on the geodetic distance and offers a number of advantages, since it allows for recursive computation and, consequently, rapid image processing. The quality of image restoration by the proposed algorithm increases as a function of the number of image channels, which is important for restoration of multispectral images. Several criteria are used to estimate the quality of image restoration.
作者简介
V. Karnaukhov
Kharkevich Institute for Information Transmission Problems
编辑信件的主要联系方式.
Email: vnk@iitp.ru
俄罗斯联邦, Moscow, 127051
M. Mozerov
Kharkevich Institute for Information Transmission Problems
Email: vnk@iitp.ru
俄罗斯联邦, Moscow, 127051