Abstract
In this paper, we first analyze a computationally efficient nonlinear edge-preserving smoothing filter, the sigma filter, in the framework of robust estimation. The sigma filter is nearly W-estimator using the metric trimming influence function with a subtle difference. Based on the analysis, we further develop another form of sigma filter as M-estimator of robust estimation using the same metric trimming influence function. The new form of sigma filter is more suitable for hardware implementation. We also compare the sigma filter with other nonlinear edge-preserving filters such as bilateral filter and median filter, in the framework of robust estimation. Finally, experimental results are reported and discussed.
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