Current estimation from satellite image sequence with global similarity optimization model

Abstract

A new approach for current tracking from a satellite image sequence is proposed to address the issue of radiometric variations between two-frame images. A global similarity criterion (GSC) is defined based on the cross correlation between two images to convert a convex optimization model to a non-convex one. The retrieval of the motion field with the criterion of the maximum similarity becomes solving a nonlinear minimization problem. One of the generic iterative equations is formulated based on the Global Similarity Optimization Model (GSOM) and a unified adaptive framework. The approach is tested using an ocean simulation dataset and realistic satellite infrared image sequences. Experimental results indicate that the new approach is not only robust for radiometric variations between two images, but also efficient, fast, and accurate for motion estimation.