DocumentCode
2500446
Title
Tensor-Driven Hyperspectral Denoising: A Strong Link for Classification Chains?
Author
Martín-Herrero, Julio ; Ferreiro-Armán, Marcos
Author_Institution
Dept. Signal Theor. & Commun., Univ. of Vigo, Vigo, Spain
fYear
2010
fDate
23-26 Aug. 2010
Firstpage
2820
Lastpage
2823
Abstract
We show how a tensor-driven anisotropic diffusion denoising method affects the performance of a classifier trained to discriminate among vine varieties in noisy hyper spectral images. We compare the classification statistics on the original and denoised images and discuss the convenience of this kind of preprocessing for classification in hyperspectral images.
Keywords
image classification; image denoising; tensors; classification chain; classification statistics; denoised image; hyperspectral image classification; noisy hyper spectral image; tensor-driven anisotropic diffusion denoising; tensor-driven hyperspectral denoising; Anisotropic magnetoresistance; Hypercubes; Hyperspectral imaging; Noise reduction; Pixel; Support vector machines; anisotropic diffusion; denoising; hyperspectral imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location
Istanbul
ISSN
1051-4651
Print_ISBN
978-1-4244-7542-1
Type
conf
DOI
10.1109/ICPR.2010.691
Filename
5597053
Link To Document