Efficient stellar spectral type classification for SDSS based on nonnegative matrix factorization

Jinfu Yang; Zhongtian Liu; Fuchao Wu

doi:10.1117/12.750756

15 November 2007 Efficient stellar spectral type classification for SDSS based on nonnegative matrix factorization

Jinfu Yang, Zhongtian Liu, Fuchao Wu

Proceedings Volume 6788, MIPPR 2007: Pattern Recognition and Computer Vision; 678824 (2007) https://doi.org/10.1117/12.750756
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

The problem of identifying spectra collected by large sky survey telescope is urgent to study to help astronomers discover new celestial bodies. Due to spectral data characteristics of high-dimension and volume, principle component analysis (PCA) technique is commonly used for extracting features and saving operations. Like many other matrix factorization methods, PCA lacks intuitive meaning because of its negativity. In this paper, non-negative matrix factorization (NMF) technique distinguished from PCA by its use of nonnegative constrains is applied to stellar spectral type classification. Firstly, NMF was used to extract features and compress data. Then an efficient classifier based on distance metric was designed to identify stellar types using the compressed data. The experiment results show that the proposed method has good performance over more than 70,000 real stellar data of Sloan Digital Sky Survey (SDSS). And the method is promising for large sky survey telescope projects.

Citation Download Citation

Jinfu Yang, Zhongtian Liu, and Fuchao Wu "Efficient stellar spectral type classification for SDSS based on nonnegative matrix factorization", Proc. SPIE 6788, MIPPR 2007: Pattern Recognition and Computer Vision, 678824 (15 November 2007); https://doi.org/10.1117/12.750756

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available