An adaptive reconstruction system for spatially correlated multispectral multitemporal images

Author

Lee, Sanghoon ; Crawford, M.M.

Author_Institution

Dept. of Ind. Eng., Kyung Won Univ., Seongnam, South Korea

Volume

29

Issue

4

fYear

1991

fDate

7/1/1991 12:00:00 AM

Firstpage

494

Lastpage

508

Abstract

An adaptive image reconstruction system has been developed to analyze sequential images observed at regular time intervals. A least-squares linear prediction with escalator structure has been implemented in this system. Using the predictor, estimates of missing data or bad (possibly cloud-covered) data and spatial parameters at a specified time can be obtained from previous history. This algorithm recovers from observations which are contaminated due to blurring and correlated noise by using temporally adapted spatial parameters

Keywords

computerised pattern recognition; computerised picture processing; geophysical techniques; geophysics computing; remote sensing; adaptive image reconstruction system; bad data estimates; blurred images processing; cloud-covered data; contaminated images data recovery; correlated noise; escalator structure; least-squares linear prediction; linear predictor; missing data estimates; remote sensing images; sequential images analysis; spatial parameters; spatially correlated multispectral multitemporal images; temporally adapted spatial parameters; Adaptive systems; Autocorrelation; Bayesian methods; History; Image analysis; Image reconstruction; Image sequence analysis; Information analysis; Parameter estimation; Remote sensing;

fLanguage

English

Journal_Title

Geoscience and Remote Sensing, IEEE Transactions on

Publisher

ieee

ISSN

0196-2892

Type

jour

DOI

10.1109/36.135811

Filename

135811