Neigh-Shrink de-noising based on Bayes-Shrink in monocular visual navigation
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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.
[1] Liu Qing,et al. SHP Component Dynamic Deployment Scheme Based on SCA , 2012 .
[2] K. C. Chou,et al. Multiscale recursive estimation, data fusion, and regularization , 1994, IEEE Trans. Autom. Control..
[3] Martin Vetterli,et al. Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..
[4] David L. Donoho,et al. De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.