Invariant subpixel material detection in hyperspectral imagery

IEEE Transactions on Geoscience and Remote Sensing

Volumn 40, Issue 3, 2002, Pages 599-608

  Thai, Bea ^b   Healey, Glenn ^a,b  

^a IEEE   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Detection; HYDICE; Hyperspectral; Invariant; Subpixel

Indexed keywords

HYPERSPECTRAL IMAGERY;

ALGORITHMS; DATA REDUCTION; IMAGE ANALYSIS; IMAGE SENSORS; LIGHT REFLECTION; MAXIMUM LIKELIHOOD ESTIMATION; SPECTRUM ANALYSIS;

REMOTE SENSING;

EID: 0036508022     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2002.1000320     Document Type: Article

References (15)

1. Spectral mixture modeling: A new analysis of rock and soil types at the Viking Lander 1 site
2. HYDICE system: Implementation and performance
3. Hyperspectral image classification and dimensionality reduction: An orthogonal subspace projection approach
4. Models and methods for automated material identification in hyperspectral imagery acquired under unknown illumination and atmospheric conditions
5. Interference-invariant target detection in hyperspectral images
6. Analysis of HYDICE noise characteristics and their impact on subpixel object detection
7. Combining linear and nonlinear processes for multispectral material detection/identification
8. Reliably estimating the noise in AVIRIS hyperspectral images
9. Matched subspace detectors
10. Multidimensional signal processing for electrooptical target detection
11. The airborne visible/infrared imaging spectrometer (AVIRIS)