Title :
Comments on "The least-squares mixing models to generate fraction images derived for remote sensing multispectral data" by Y.E. Shimabukuro and J.A. Smith
Author :
Schanzer, Dena L.
Author_Institution :
Stat. Consulting Centre, Carleton Univ., Ottawa, Ont., Canada
fDate :
5/1/1993 12:00:00 AM
Abstract :
The commenter notes that in the above-titled paper, Y.E. Shimabukuro and J.A. Smith (ibid., vol.29, pp.16-20, Jan 1991) address the issue of numerical solutions to the problem of constraining the mixture proportions to the zero one interval and ensuring that the sum of proportions is equal to one. The commenter suggests a method whereby unconstrained stepwise regression can be used as an alternative to constrained regression, made possible by a redesign of the design matrix. In addition, each constraint represents a testable hypothesis, providing information that may be used in endmember or component selection, or in evaluating the overall model fit.<>
Keywords :
image reconstruction; least squares approximations; remote sensing; component selection; design matrix; fraction images; least-squares mixing models; mixture proportions; remote sensing multispectral data; unconstrained stepwise regression; zero one interval; Image analysis; Image generation; Layout; Pixel; Reflectivity; Remote sensing; Statistics; Terminology; Testing; Vectors;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on