A. Y. Denisova, Y. N. Juravel, V. V. Myasnikov, “Estimation of parameters of a linear spectral mixture for hyperspectral images with atmospheric distortions”, Computer Optics, 2016, Volume 40, Issue 3,Pages <nobr>380

This article is cited in 10 papers

HUPERSPECTRAL DATA ANALYSIS

Estimation of parameters of a linear spectral mixture for hyperspectral images with atmospheric distortions

A. Y. Denisova^a, Y. N. Juravel^a, V. V. Myasnikov^ba

^a Samara National Research University, Samara, Russia
^b Image Processing Systems Institute оf RAS,– Branch of the FSRC “Crystallography and Photonics” RAS, Samara, Russia

Abstract: In this paper, we propose a novel method for estimating parameters of a linear spectral mixture for hyperspectral images. This method allows omitting a preliminary atmospheric correction of the input image. In order to derive a solution of the mixture problem different models of radiation transmission in atmosphere are considered. An evaluation of the effects of noise, the number of input pixels, and the number of signatures on the accuracy of the linear mixture coefficient restoration and the input pixel representation error is made.

Keywords: hyperspectral images, linear spectral mixture analysis, atmospheric correction.

Received: 28.04.2016
Accepted: 13.05.2016

DOI: 10.18287/2412-6179-2016-40-3-380-387