DocumentCode
1515626
Title
On the Convergence of N-FINDR and Related Algorithms: To Iterate or Not to Iterate?
Author
Dowler, Shaun ; Andrews, Mark
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Auckland, Auckland, New Zealand
Volume
8
Issue
1
fYear
2011
Firstpage
4
Lastpage
8
Abstract
A popular algorithm for unmixing hyperspectral data, namely, Winter´s N-FINDR algorithm, is frequently used to benchmark other algorithms or as the basis for new algorithms. The interpretations of this algorithm within the literature are not consistent, and some of these differences have significant impact on the convergence of the algorithm. Despite this, the differences in implementation have not been explicitly acknowledged within the literature, which means that many studies are now ambiguous or incomparable. An examination of various implementations of the N-FINDR algorithm highlights that not all interpretations possess the properties asserted by Winter and that interpretations that consider each pixel multiple times generate much larger simplexes. Regardless of which implementation researchers choose to use, if they are explicit in their choice, this would allow for unambiguous comparisons.
Keywords
algorithm theory; N-FINDR algorithm; algorithm convergence; unmixing hyperspectral data; Algorithm design and analysis; Convergence; Gaussian noise; Hyperspectral imaging; Layout; Solid modeling; Vectors; Hyperspectral; N-FINDR; unmixing;
fLanguage
English
Journal_Title
Geoscience and Remote Sensing Letters, IEEE
Publisher
ieee
ISSN
1545-598X
Type
jour
DOI
10.1109/LGRS.2010.2049639
Filename
5484534
Link To Document