DocumentCode
2448559
Title
Improving locally weighted denoising method for hyperspectral data in spectral domain
Author
Jiang, Lili ; Li, Junwei ; Wang, Guangping ; Lu, Yi
Author_Institution
Sci. & Technol. on Opt. Radiat. Lab., Beijing, China
fYear
2011
fDate
24-26 June 2011
Firstpage
2218
Lastpage
2220
Abstract
An improved method of locally weighted denoising is introduced and applied to hyperspectal imagery denoising in spectral domain. Weight factors and incidence are self-defined in the method. During the processing, it remains more spectral details for hyperspectral data compared with the conventional weighted averaging method. Experimental results show that the proposed algorithm of locally weighted denoising provides an improvement in SNR for hyperspectal data specially.
Keywords
image denoising; statistical analysis; SNR; hyperspectal imagery denoising; locally weighted denoising method; spectral domain; Discrete wavelet transforms; Geoscience; Hyperspectral imaging; Image denoising; Noise reduction; Optical imaging; Spectral analysis; denoising; hyperspectal data; locally weighted;
fLanguage
English
Publisher
ieee
Conference_Titel
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-9172-8
Type
conf
DOI
10.1109/RSETE.2011.5964749
Filename
5964749
Link To Document