Geometric Distortion Correction of Airborne Multispectral Scanner Data

Geometric Correction of ERTS-1 Digital Multispectral Scanner Data

Continuous Piecewise Geometric Rectification for Airborne Multispectral Scanner Imagery

Geometric rectification of airborne multispectral scanner image data using traditional polynomial functions often cannot provide satisfactory RMSE accuracy due to the complex nature of geometric distortions in the data. The discrete approach to rectifying these data generates segmented pieces that may cause edge-matching problems after they are reassembled. To improve the rectification accuracy...

Discrimination of arid vegetation with airborne multispectral scanner hyperspectral imagery

Hyperspectral imagery from the airborne multispectral scanner was evaluated for discrimination and mapping of vegetation components in a semi-arid rangeland environment in Southern Australia. Automated unmixing of two image strips with 5-m resolution revealed several vegetation endmembers in the visible, near infrared (near-IR), and short-wave infrared portions of the imagery. Identity of the e...

Mineralogic information from a new airborne thermal infrared multispectral scanner.

A new six-channel aircraft multispectral scanner has been developed to exploit mineral signature information at wavelengths between 8 and 12 micrometers. Preliminary results show that igneous rock units can be identified from their free silica content, and that carbonate as well as clay-bearing units are readily separable on the digitally processed images.

Hierarchical Classification of Multitemporal/Multispectral Scanner Data

Most techniques for computer classification of multispectral scanner data involve a "single-stage" approach in which every pixel in the data is classified in a single step, using a single set of training statistics and a single set of wave length bands. Hierarchical classifiers, on the other hand, involve a sequence of classification steps, each of which can involve a different wavelength band ...