论文信息 - Order Statistical Filtering: a Robust Method of Noise Estimation

Order Statistical Filtering: a Robust Method of Noise Estimation

Abstract The detection of a narrowband signal in a sonar environment with spatially uncorrelated white noise depends very much on the accuracy in estimating the noise power so that a threshold can be correctly fixed. The conventional MA method presents a large bias when operated in an environment where interfering signals exist in the neighborhood. Various types of nonlinear methods based on the use of order statistics are introduced and analyzed and are found to be much more robust.

Kon Max Wong | K. M. Wong

[1] K. M. Wong,et al. Some statistical properties of median filters , 1981 .

[2] Lawrence R. Rabiner,et al. Applications of a nonlinear smoothing algorithm to speech processing , 1975 .

[3] John W. Tukey,et al. Nonlinear (nonsuperposable) methods for smoothing data , 1974 .

[4] Nuggehally Sampath Jayant. Average- and Median-Based Smoothing Techniques for Improving Digital Speech Quality in the Presence of Transmission Errors , 1976, IEEE Trans. Commun..

[5] B I Justusson,et al. Median Filtering: Statistical Properties , 1981 .

[6] W. N. Venables,et al. Permanent Expressions for Order Statistic Densities , 1972 .

[7] G. Wise,et al. A theoretical analysis of the properties of median filters , 1981 .

[8] J. Bednar,et al. Alpha-trimmed means and their relationship to median filters , 1984 .

[9] Thomas S. Huang,et al. A generalization of median filtering using linear combinations of order statistics , 1983 .

[10] T. Nodes,et al. Median filters: Some modifications and their properties , 1982 .

[11] F. Kuhlmann,et al. On Second Moment Properties of Median Filtered Sequences of Independent Data , 1981, IEEE Trans. Commun..