Full Content is available to subscribers

Subscribe/Learn More  >
Proceedings Article

Improved sequential search algorithms for classification in hyperspectral remote sensing images

[+] Author Affiliations
Songyot Nakariyakul

Thammasat Univ. (Thailand)

Proc. SPIE 9273, Optoelectronic Imaging and Multimedia Technology III, 927328 (November 5, 2014); doi:10.1117/12.2075281
Text Size: A A A
From Conference Volume 9273

  • Optoelectronic Imaging and Multimedia Technology III
  • Qionghai Dai; Tsutomu Shimura
  • Beijing, China | October 09, 2014

abstract

Two new sequential search algorithms for feature selection in hyperspectral remote sensing images are proposed. Since many wavebands in hyperspectral images are redundant and irrelevant, the use of feature selection to improve classification results is highly needed. First, we present a new generalized steepest ascent (GSA) feature selection technique that improves upon the prior steepest ascent algorithm by selecting a better starting search point and performing a more thorough search. It is guaranteed to provide solutions that equal or exceed those of the classical sequential forward floating selection algorithm. However, when the number of available wavebands is large, the computational load required for the GSA algorithm becomes excessive. We thus propose a modification of the improved floating forward selection algorithm which is more computationally efficient. Experimental results for two hyperspectral data sets show that our proposed algorithms yield better classification results than other suboptimal search algorithms. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation

Songyot Nakariyakul
" Improved sequential search algorithms for classification in hyperspectral remote sensing images ", Proc. SPIE 9273, Optoelectronic Imaging and Multimedia Technology III, 927328 (November 5, 2014); doi:10.1117/12.2075281; http://dx.doi.org/10.1117/12.2075281


Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).

Figures

Tables

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging & repositioning the boxes below.

Related Book Chapters

Topic Collections

Advertisement
  • Don't have an account?
  • Subscribe to the SPIE Digital Library
  • Create a FREE account to sign up for Digital Library content alerts and gain access to institutional subscriptions remotely.
Access This Proceeding
Sign in or Create a personal account to Buy this proceeding ($15 for members, $18 for non-members).
Access This Proceeding
Sign in or Create a personal account to Buy this article ($15 for members, $18 for non-members).
Access This Chapter

Access to SPIE eBooks is limited to subscribing institutions and is not available as part of a personal subscription. Print or electronic versions of individual SPIE books may be purchased via SPIE.org.