An new algorithm of infrared moving small targets recognition

Abstract

Detection and recognition of the dim moving small targets in the infrared image sequences containing cloud clutter is an important research area, especially for Infrared Search and Track surveillance applications. In the paper, the author propose a new algorithm having high performance for detecting moving small targets in infrared image sequences containing cloud clutter. The novelty of the algorithm is that it fuses the features of the moving small targets in both the spatial domain and temporal domain. Two independent units can realize the calculative process. Another advantage of the method is that it can get the better detection precision than some other methods. We also present the algorithm based on image fusion and Kalman tracking that can track a number of very small, low constant objects through an image sequence taken from a static camera.

Automated object extraction from remote sensor image based on adaptive thresholding technique

“…Wavelet filters have been proven to be superior to Fourier methods for detecting localized high frequency behavior in an otherwise predominantly low frequency signal [7] . Another advantage of using the wavelet filters is that they are robust to noise.…”