Landsat spectral demixing a la superresolution of blind matrix inversion by constraint MaxEnt neural nets

Harold H. Szu; Charles C. Hsu

doi:10.1117/12.271711

3 April 1997 Landsat spectral demixing a la superresolution of blind matrix inversion by constraint MaxEnt neural nets

Harold H. Szu, Charles C. Hsu

Proceedings Volume 3078, Wavelet Applications IV; (1997) https://doi.org/10.1117/12.271711
Event: AeroSense '97, 1997, Orlando, FL, United States

Abstract

A single pixel of a Landsat image has seven channels receiving 0.1 to 10 microns of radiation from the ground within a 20 by 20 meter footprint. In principle, the pattern of seven values can be utilized to identify ground sources within the pixel footprint by using methodologies called spectral blind demixing of unknown sources when the reflectance matrix W_ij for the ith object and the jth band is either partially or difficult to measure in the outer space.

Citation Download Citation

Harold H. Szu and Charles C. Hsu "Landsat spectral demixing a la superresolution of blind matrix inversion by constraint MaxEnt neural nets", Proc. SPIE 3078, Wavelet Applications IV, (3 April 1997); https://doi.org/10.1117/12.271711

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