Experimental Approach to the Selection of the Components in the Minimum Noise Fraction

被引：43

作者：

Amato, Umberto ^{[1
]}

Cavalli, Rosa Maria ^{[2
]}

Palombo, Angelo ^{[3
]}

Pignatti, Stefano ^{[3
]}

Santini, Federico ^{[2
]}

机构：

[1] Italian Natl Res Council, Inst Applicat Calculus, I-80131 Naples, Italy

[2] Italian Natl Res Council, Inst Atmospher Pollut, Airborne Lab Environm Res, I-00016 Rome, Italy

[3] Italian Natl Res Council, Inst Methodol Environm Anal, I-85050 Potenza, Italy

来源：

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2009年 / 47卷 / 01期

关键词：

Image enhancement; image processing; image restoration; noise; remote sensing; MULTISPECTRAL DATA; NUMBER;

D O I：

10.1109/TGRS.2008.2002953

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

An experimental method to select the number of principal components in minimum noise fraction (MNF) is proposed to process images measured by imagery sensors onboard aircraft or satellites. The method is based on an experimental measurement by spectrometers in dark conditions from which noise structure can be estimated. To represent typical land conditions and atmospheric variability, a significative data set of synthetic noise-free images based on real Multispectral Infrared and Visible Imaging Spectrometer images is built. To this purpose, a subset of spectra is selected within some public libraries that well represent the simulated images. By coupling these synthetic images and estimated noise, the optimal number of components in MNF can be obtained. In order to have an objective (fully data driven) procedure, some criteria are proposed, and the results are validated to estimate the number of components without relying on ancillary data. The whole procedure is made computationally feasible by some simplifications that are introduced. A comparison with a state-of-the-art algorithm for estimating the optimal number of components is also made.

引用

页码：153 / 160

页数：8

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