Methods for improving accuracy, analyzing change detection, and performing data compression for multiple images

Abstract

A multi-temporal, multi-angle, automated target exploitation method is provided for processing a large number of images. The system geo-rectifies the images to a three-dimensional surface topography, co-registers groups of the images with fractional pixel accuracy, automates change detection, evaluates the significance of change between the images, and massively compresses imagery sets based on the statistical significance of change. The method improves the resolution, accuracy, and quality of information extracted beyond the capabilities of any single image, and creates registered six-dimensional image datasets appropriate for mathematical treatment using standard multi-variable analysis techniques from vector calculus and linear algebra such as time-series analysis and eigenvector decomposition.

What is claimed is: 
     
         1 . A system for analyzing and improving accuracies of two-dimensional images and for forming three-dimensional images from the two-dimensional images, the system comprising:
 a processor; and   a memory that includes a plurality of two-dimensional images and instructions, the plurality of two-dimensional images each including a same target area and being acquired at same or different times and at different collection angles, the instructions configured to, when executed by the processor, cause the processor to execute operations comprising;
 correlating a plurality of target features in the target area of each of the two-dimensional images; 
 determining, independently for each of the plurality of two-dimensional images and based on image pointing parameters, a three-dimensional geolocation position for each of the plurality of target features; 
 calculating a weighted average or a least squares fitting of the three-dimensional geolocation position for each of the plurality of target features using the plurality of two-dimensional images; 
 adjusting, variably across each of the plurality of two-dimensional images, the image pointing parameters by providing an adjustment of the image pointing parameters to minimize a geolocation difference between the three-dimensional geolocation position of each of the plurality of target features in each of the plurality of two-dimensional images and the weighted average or the least squares fitting of the three-dimensional geolocation position of each of the plurality of target features across the plurality of two-dimensional images; and 
 projecting each of the plurality of two-dimensional images onto a georeferenced three-dimensional surface model of the target area based on results of the adjusting to form georeferenced three-dimensional images from the plurality of two-dimensional images.