Weighted Repeated Median Smoothing and Filtering

Weighted Repeated Median Smoothing and Filtering

An Efficient Design Method for Optimal Weighted Median Filtering

Earlier research has shown that the problem of optimal weighted median filtering with structural constraints can be formulated as a nonconvex nonlinear programming problem in general. However, its high computational complexity and poor performance due to its nonconvex nature prohibit it from practical applications. In this paper, we shall show that the design problem can be formulated as a conv...

Bayesian Filtering and Smoothing

Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). Interest in these methods has exploded in recent years, with numerous applications emerging in fields such as navigation, aerospace engineering, telecommunications, and medicine. This compact, informal introduction for graduate students an...

Mesh Smoothing via Mean and Median Filtering Applied to Face Normals

In this paper, we introduce iterative mean and median filtering schemes for smoothing noisy 3D shapes given as triangle meshes. Our main idea consists of applying mean and median filtering schemes to mesh normals and then update the mesh vertex position in order to fit the mesh to the modified normals. We also give a quantitative evaluation of the proposed mesh filtering schemes and compare the...

Repeated median and hybrid filters

Standard median filters preserve abrupt shifts (edges) and remove impulsive noise (outliers) from a constant signal but they deteriorate in trend periods. FIR median hybrid (FMH) filters are more flexible and also preserve shifts, but they are much more vulnerable to outliers. Application of robust regression methods, in particular of the repeated median, has been suggested for removing subsequ...