Sparsity Promoting Iterated Constrained Endmember Detection in Hyperspectral Imagery

  title={Sparsity Promoting Iterated Constrained Endmember Detection in Hyperspectral Imagery},
  author={Alina Zare and Paul D. Gader},
  journal={IEEE Geoscience and Remote Sensing Letters},
An extension of the iterated constrained endmember (ICE) algorithm that incorporates sparsity-promoting priors to find the correct number of endmembers is presented. In addition to solving for endmembers and endmember fractional maps, this algorithm attempts to autonomously determine the number of endmembers that are required for a particular scene. The number of endmembers is found by adding a sparsity-promoting term to ICE's objective function. 
Highly Influential
This paper has highly influenced 10 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 135 citations. REVIEW CITATIONS
95 Citations
8 References
Similar Papers


Publications citing this paper.
Showing 1-10 of 95 extracted citations

135 Citations

Citations per Year
Semantic Scholar estimates that this publication has 135 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-8 of 8 references

Fast autonomous spectral end-member determination in hyperspectral data

  • M. E. Winter
  • Proc. 13th Int. Conf. Appl. Geologic Remote Sens…
  • 1999
Highly Influential
3 Excerpts

Mapping target signatures via partial unmixing of AVIRIS data

  • J. Boardmann, F. Kruse, R. Green
  • Proc. Summaries 5th Annu. JPL Airborne Geosci…
  • 1995
3 Excerpts

Similar Papers

Loading similar papers…