Title :
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
fDate :
7/1/1991 12:00:00 AM
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;
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
