Abstract

A new (to our knowledge) theory of component pattern analysis in multispectral images is developed by using the methods of principal component analysis and nonlinear optimization with a nonnegativity constraint. Given images of a scene in different color bands, we estimate both the spectral curves of components included in the image and the spatial pattern corresponding to each spectral curve. In this method, neither spatial nor spectral features of the components are necessary, but the physical rule of nonnegative absorptivity and density nonnegativity is used for any material of any optical frequency at any position in the image. Experimental results of component analysis with real microscopic image data are shown to demonstrate the effectiveness of the proposed method.

© 1987 Optical Society of America

PDF Article

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription