A method to generate sub-pixel classification maps for use in DIRSIG three-dimensional models

摘要

Developing new remote sensing instruments is a costly and time consuming process. The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model gives users the ability to create synthetic images for a proposed sensor before building it. However, to produce synthetic images, DIRSIG requires facetized, three-dimensional models attributed with spectral and texture information which can themselves be costly and time consuming to produce. Recent work has been successful in generating these scenes using an automated method when coincident HyperSpectral Imagery (HSI), Light Detection and Ranging (LIDAR), and high-resolution imagery of a site are available. An important step in this process is attributing the three-dimensional information gained from the LIDAR with spectral information gained from the HSI. Previous work was able to do this attribution at the resolution of the HSI, but the HSI is generally at the lowest resolution of the three modalities. Due to the highly accurate method used to register the HSI, LIDAR, and high-resolution imagery, the potential for bringing additional information into the classification process exists. This paper will present a method to generate classification maps at or near the resolution of the high-resolution imagery component of the fused imagery. Initial results using this new method are provided and are promising in terms of their ability to ultimately help produce higher fidelity DIRSIG models.