Removing Noise and Preserving Details with Relaxed Median Filters
Journal of Mathematical Imaging and Vision
Selection weighted vector directional filters
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
A method based on rank-ordered filter to detect edges in cellular image
Pattern Recognition Letters
Steerable weighted median filters
IEEE Transactions on Image Processing
Noiseless codelength in wavelet denoising
EURASIP Journal on Advances in Signal Processing
A new adaptive median filtering technique for removal of impulse noise from images
Proceedings of the 2011 International Conference on Communication, Computing & Security
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A new expression for the output moments of weighted median filtered data is derived. The noise attenuation capability of a weighted median filter can now be assessed using the L-vector and M-vector parameters in the new expression. The second major contribution of the paper is the development of a new optimality theory for weighted median filters. This theory is based on the new expression for the output moments, and combines the noise attenuation and some structural constraints on the filter's behavior. In certain special cases, the optimal weighted median filter can be obtained by merely solving a set of linear inequalities. This leads in some cases to closed form solutions for optimal weighted median filters. Some applications of the theory developed in this paper, in 1-D signal processing and image processing are discussed. Throughout the analysis, some striking similarities are pointed out between linear FIR filters and weighted median filters