Tropical cyclone (TC) center locating is crucial because it lays the foundation for TC forecasting. Locating TC centers, usually by manual means, continues to present many difficulties. Not least is the problem of inconsistency between TC center locations forecast by different agencies. In this paper, an objective TC center locating scheme is developed, using infrared satellite images. We introduce a pattern-matching concept, which we illustrate using a spiral curve model. A spiral band model, based on a spiral band region, is designed to extract the spiral cloud-rain bands (SCRBs) of TCs. We propose corresponding criteria on which to score the fitting value of a candidate template defined by our models. In the proposed scheme, TC location is an optimization problem, solved by an ant colony optimization algorithm. In numerical experiments, a minimal mean distance error of 17.9 km is obtained when the scheme is tested against best-track data. The scheme is suitable for TCs with distinct SCRBs or symmetrical central dense overcast, and for TCs both with and without clear eyes.
BAI QiuChanWEI KunJING ZhongLiangLI YuanXiangTUO HongYaLIU ChengGang
Image fusion can be performed at different levels:signal,pixel,feature and symbol levels.Almost all image fusion algorithms developed to date fall into pixel level.This paper provides an overview of the most widely used pixel-level image fusion algorithms and some comments about their relative strengths and weaknesses.Particular emphasis is placed on multiscale-based methods.Some performance measures practicable for pixel-level image fusion are also discussed.At last,prospects of pixel-level image fusion are made.
