Using a New Search Strategy to Improve the Performance of N-FINDR Algorithm for End-Member Determination

A new search strategy proposed in this paper, which is used in n-dimensional spectral feature space to find reasonable end-members based on maximum volume transform (MVT), is implemented to improve the performance of N-FINDR algorithm. The N-FINDR algorithm, as a successfully used end-member extract...

Full description

Saved in:
Bibliographic Details
Published in2009 2nd International Congress on Image and Signal Processing pp. 1 - 4
Main Authors Ying Wang, Lei Guo, Nan Liang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2009
Subjects
Algorithm design and analysis
Automation
Business
Data mining
Feature extraction
Hyperspectral imaging
Hyperspectral sensors
Iterative algorithms
Pixel
Stability
Online AccessGet full text
ISBN1424441293
9781424441297
DOI10.1109/CISP.2009.5301014

Cover

More Information
Summary:A new search strategy proposed in this paper, which is used in n-dimensional spectral feature space to find reasonable end-members based on maximum volume transform (MVT), is implemented to improve the performance of N-FINDR algorithm. The N-FINDR algorithm, as a successfully used end-member extraction tool, produces inconsistent result in many cases and consumes lots of computing time if it carries out exhaustive search. In order to reduce the computation complexity and enhance the stability of N-FINDR, this search strategy is developed to eliminate most sample vectors, each of which is involved in computation unnecessarily, and select potential end-members sequentially. The new version N-FINDR algorithm with the search strategy presented in this paper will save computing time significantly and perform as well as original N-FINDR algorithm for end-member extraction, even better.
ISBN:1424441293
9781424441297
DOI:10.1109/CISP.2009.5301014