Dim Moving Small Target Detection by Local and Global Variance Filtering on Temporal Profiles in Infrared Sequences

In this paper, the temporal different characteristics between the target and background pixels are used to detect dim moving targets in the slow-evolving complex background. A local and global variance filter on temporal profiles is presented that addresses the temporal characteristics of the target and background pixels to eliminate the large variation of background temporal profiles. Firstly, the temporal behaviors of different types of image pixels of practical infrared scenes are analyzed.Then, the new local and global variance filter is proposed. The baseline of the fluctuation level of background temporal profiles is obtained by using the local and global variance filter. The height of the target pulse signal is extracted by subtracting the baseline from the original temporal profiles. Finally, a new target detection criterion is designed. The proposed method is applied to detect dim and small targets in practical infrared sequence images. The experimental results show that the proposed algorithm has good detection performance for dim moving small targets in the complex background.

Distributed cooperative localization for sparse communication network with multi-locating messages

In cooperative localization with sparse communication networks, an agent maybe only receives part of locating messages from the others. It is difficult for the receiver to utilize the part instead of global knowledge. Under the extended Kalman filtering, the utilization of the locating message is maximized by two aspects： the locating message generating and multi-locating messages fusing. For the former, the covariance upper-bound technique, by introducing amplification coefficients, is employed to remove the dependency of locating messages on the global knowledge. For the latter, an optimization model is setup; the covariance matrix determinant of the receiver＇s state estimate, expressed as a function of the amplification coefficients, is selected as the optimization criterion, under linear constraints on the amplification coefficient characteristics and the communication connectivity. Using the optimization solution, the local optimal state of the receiver agent is obtained by the weighting fusion. Simulation with seven agents is shown to evaluate the effectiveness of the proposed algorithm.