Abstract: A novel morphology de-noising method, i.e., adaptive multi-scale morphological analysis algorithm, is proposed based on mathematical morphology for the noise interference introduced in the acquisition process of the firearms' shoulder-force signals. The open-closing and close-opening operations are used to extract the positive and negative impacts from noisy signals. According to the statistical distribution of noises, the results of morphological analysis for different scales are weighted and averaged, and the contradiction between detail preserving and noise filtering is resolved. Blocks signal in Gaussian white noises is studied through simulation, and the de-noising performance of the proposed method is measured by examining the signal noise ratio and mean square error. The results show that the proposed method is able effectively to suppress Gaussian white noises while preserving the features of blocks signal. Key

Key words: ordnancescienceandtechnology, shoulder-forcesignal, mathematicalmorphology, morphologyfiltering, adaptivemulti-scale, de-noising