K. Palaniappan, C. Kambhamettu, A. F. Hasler, and D. B. Goldgof

Proc. 5th IEEE Int. Conf. Computer Vision, pgs. 659--665, 1995

motion, tracking, stereo, visualization, cloud, remote sensing

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Abstract

Time-varying multispectral observations of clouds from meteorological satellites are used to estimate cloud-top heights (structure) and cloud winds (semi-fluid motion). Stereo image pairs over several time steps were acquired by two geostationary satellites with synchronized scanning instruments. Cloud-top height estimation from these image pairs is performed using an improved automatic stereo analysis algorithm on a massively parallel Maspar computer with 16 K processors. A new category of motion behavior known as semi-fluid motion is described for modeling cloud motions and an automatic algorithm for extracting semi-fluid motion is developed to track cloud winds. The time sequential dense estimates of cloud-top height depth maps in conjunction with intensity data are used to estimate local semi-fluid motion parameters for cloud tracking. Both stereo disparities and motion correspondences are estimated to sub-pixel accuracy. The Interactive Image SpreadSheet (IISS) is a new versatile visualization tool that was enhanced to analyze and visualize the results of the stereo analysis and semi-fluid motion estimation algorithms. Experimental results using time-varying data of the visible channel from two satellites in geosynchronous orbit is presented for the Hurricane Frederic