Neigh-Shrink de-noising based on Bayes-Shrink in monocular visual navigation

摘要

In view that the noise of image in monocular visual navigation, a Neigh-Shrink de-noising method based on Bayes-Shrink is proposed. First, the method uses Bayes-Shrink adaptive threshold replace common threshold as the contraction threshold of Neigh-Shrink, and then eliminate the high frequency sub-band of image obtained by monocular visual system after non-subsample Contourlet transform (NSCT) decomposition. Experiment results show that the improved Neigh-Shrink method in de-noising performance and visual effects have been improved, with better anti-noise performance and excellent edge protection, and can effectively be used in monocular visual navigation.