Fast and robust star detection algorithm based on the dyadic wavelet transform

Star detection is an important part of the spacecraft attitude determination performed by star trackers. The current advanced algorithms can effectively extract points in complex backgrounds. However, there are still two problems: first, parameters algorithm not adaptive, which limits its reliability and robustness; second, high performance low computational time usually cannot be achieved simultaneously. In this work, a rapid utilizing dyadic wavelet transform (SDDWT) was developed based on à Trous algorithm. authors constructed suitable basis applied to image. maximum coefficients at certain scale were binarized according threshold value separate stars from background. adaptively determined white Gaussian noise (WGN) power. Finally, method for separating individual developed. Experiments indicated that proposed able ensure false alarm rate value. Moreover, image 1024×1024, SDDWT stable within 0.3 s, smaller than other algorithms.