EMPIRICAL-METHODS TO COMPENSATE FOR A VIEW-ANGLE-DEPENDENT BRIGHTNESSGRADIENT IN AVIRIS IMAGERY

Citation
Re. Kennedy et al., EMPIRICAL-METHODS TO COMPENSATE FOR A VIEW-ANGLE-DEPENDENT BRIGHTNESSGRADIENT IN AVIRIS IMAGERY, Remote sensing of environment, 62(3), 1997, pp. 277-291
Citations number
34
Categorie Soggetti
Environmental Sciences","Photographic Tecnology","Remote Sensing
ISSN journal
00344257
Volume
62
Issue
3
Year of publication
1997
Pages
277 - 291
Database
ISI
SICI code
0034-4257(1997)62:3<277:ETCFAV>2.0.ZU;2-C
Abstract
A view-angle-dependent brightness gradient was observed in an AVIRIS i mage of a forested region in Oregon's Cascade Mountains. A method of r emoving the view-angle effect was sought that would not alter the radi ometric integrity of the image, and which would require minimal ancill ary information. Four methods were tested and evaluated in terms of re maining brightness gradient and in terms of retention of spectral char acteristics. All methods used a quadratic fitting equation to model th e changes in brightness across view angles. Other descriptive coeffici ents were calculated to aid in interpretation. The observed view-angle effect varied with wavelength in a manner consistent with predictions of bidirectional reflectance distribution function characteristics of vegetation. View-angle effects were determined to contain both additi ve and multiplicative components, with multiplicative components being strong in the chlorophyll absorption region. The view-angle effect in a given pixel was a function of both an underlying view-angle respons e determined by surface structure and the inherent brightness of that pixel. The most successful compensation method was the one that best a ccounted for broad differences between pixels in these two components. Despite the simplifying assumptions necessary for empirical view-angl e correction techniques, they can still be useful for hyperspectral re mote-sensing data in situations where the view-angle brightness variat ions would mask variance useful for extracting scene information. Publ ished by Elsevier Science Inc., 1997.