A method to extract spatial amplitude and variability information from remotely sensed digital imaging data is presented. High Pass Filters (HPFs) are used to compute both a Spatial Amplitude Image/Index (SAI) and Spatial Variability Image/Index (SVI) at the local, intermediate, and regional scales. Used as input to principal component analysis and automatic clustering classification, the results indicate that spatial information at scales other than local is useful in the analysis of remotely sensed data. The resultant multi-spatial data set allows the user to study and analyze an image based more on the complete spatial characteristics of an image than only local textural information.
Additional publication details
Extraction of spatial information from remotely sensed image data - an example: gloria sidescan sonar images