Publicou 12 edições por ano
ISSN Imprimir: 0040-2508
ISSN On-line: 1943-6009
Indexed in
DENOISING OF MULTICHANNEL IMAGES WITH NONLINEAR TRANSFORMATION OF REFERENCE IMAGE
RESUMO
It has been demonstrated recently that efficiency of filtering a noisy component image of a multichannel image can be sufficiently improved under condition that the multichannel image has almost noise-free component image(s) that possess high correlated with the noisy component image used as reference. High correlation and practical absence of the noise are only pre-requisites for efficient filtering of the noisy image using reference. Other criteria of similarity than cross-correlation factor are important. In this paper we show how it is possible to make the reference image very "close" to the noisy one by exploiting nonlinear transformation. Moreover, it is demonstrated that the proposed approach can be useful for denoising images corrupted by signal-dependent noise which is often the case for multichannel remote sensing data.
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Abramov Sergey, Uss Mikhail, Lukin Vladimir, Vozel Benoit, Chehdi Kacem, Egiazarian Karen, Enhancement of Component Images of Multispectral Data by Denoising with Reference, Remote Sensing, 11, 6, 2019. Crossref