Adaptive data processing procedures are applied to the problem of classifying objects in a scene scanned by multispectral sensor. These procedures show a performance improvement over standard nonadaptive techniques. Some sources of error in classification are identified and those correctable by adaptive processing are discussed. Experiments in adaptation of signature means by decision-directed methods are described. Some of these methods assume correlation between the trajectories of different signature means; for others this assumption is not made
A computational model of the processes involved in multispectral remote sensing and data classificat...
Data concerning a multidisciplinary and multi-organizational effort to implement multispectral data ...
The operational tasks of the onboard multispectral classification study were defined. These tasks in...
The applicability of recognition-processing procedures for multispectral scanner data from areas and...
Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, m...
The algorithms employed in the current ERIM data processing scheme are described. Methods for suitab...
Analytical and test results on the use of adaptive processing on LANDSAT data are presented. The Kal...
The improvement and extension of the capabilities of the Environmental Research Institute of Michiga...
Research in multispectral data processing at LARS/Purdue is directed at supporting a substantial lev...
The multispectral techniques have shown themselves capable of solving problems in a large number of ...
The development of techniques to extend spectral signatures in space and time is reported. Signature...
Method is combination of digital and optical techniques. Multispectral data is coded into binary mat...
Recent improvements in remote sensor technology carry implications for data processing. Multispectra...
A method is presented for feature extraction of multispectral scanner data. Non-training data is use...
The advantages and disadvantages of various remote sensing instrumentation and analysis techniques a...
A computational model of the processes involved in multispectral remote sensing and data classificat...
Data concerning a multidisciplinary and multi-organizational effort to implement multispectral data ...
The operational tasks of the onboard multispectral classification study were defined. These tasks in...
The applicability of recognition-processing procedures for multispectral scanner data from areas and...
Two major aspects of remote sensing with multispectral scanners (MSS) are investigated. The first, m...
The algorithms employed in the current ERIM data processing scheme are described. Methods for suitab...
Analytical and test results on the use of adaptive processing on LANDSAT data are presented. The Kal...
The improvement and extension of the capabilities of the Environmental Research Institute of Michiga...
Research in multispectral data processing at LARS/Purdue is directed at supporting a substantial lev...
The multispectral techniques have shown themselves capable of solving problems in a large number of ...
The development of techniques to extend spectral signatures in space and time is reported. Signature...
Method is combination of digital and optical techniques. Multispectral data is coded into binary mat...
Recent improvements in remote sensor technology carry implications for data processing. Multispectra...
A method is presented for feature extraction of multispectral scanner data. Non-training data is use...
The advantages and disadvantages of various remote sensing instrumentation and analysis techniques a...
A computational model of the processes involved in multispectral remote sensing and data classificat...
Data concerning a multidisciplinary and multi-organizational effort to implement multispectral data ...
The operational tasks of the onboard multispectral classification study were defined. These tasks in...