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 :
بازگشت