INCLUSION OF MULTISPECTRAL DATA INTO OBJECT RECOGNITION
Beata M. Csatho, Toni F. Schenk, Dong-Cheon Lee, Sagi Filin · 1999
In this paper, we describe how object recognition benefits from exploiting multispectral and multisensor datasets. After a brief introduction we summarize the most important principles of object recognition and multisensor fusion. This serves as the basis for the proposed architecture of a multisensor object recognition system. It is characterized by multistage fusion, where the different sensory input data are processed individually and only merged at appropriate levels. The remaining sections describe the major fusion processes. Rather than providing detailed descriptions, a few examples, obtained from the Ocean City test-data site, have been chosen to illustrate the processing of the major data streams. The test site comprises of multispectral and aerial imagery, and laser scanning data. 1. INTRODUCTION The ultimate goal of digital photogrammetry is the automation of map making. This entails understanding aerial imagery and recognizing objects - both hard problems. Despite of the ...