What are the MLV and MCV filters?

The Mean of Least Variance (MLV) filter is an edge-preserving (actually edge-enhancing) noise smoothing filter based on the concepts of mathematical morphology. I'm hoping to put together a decent description of it for this page in the near future. Basically the idea is to smooth an image only over areas that have a low variance - that is, areas that are most nearly homogeneous and do not contain edges or other features. The MCV filter is similar, except that it uses the Coefficient of Variation rather than the variance to perform better on multiplicative noise. Details are found in the following references:

References for the MLV filter:

Mark A. Schulze. "Biomedical Image Processing with Morphology-Based Nonlinear Filters." Ph.D. dissertation, The University of Texas at Austin, 1994. The Abstract and Table of Contents are available.

M. A. Schulze and J. A. Pearce. "A morphology-based filter structure for edge-enhancing smoothing." Proc. of the 1994 IEEE International Conference on Image Processing (ICIP-94), pp. 530-534. (Austin, Texas, Nov. 13-16, 1994.) The abstract for this paper is available.

M. A. Schulze and J. A. Pearce. "Value-and-criterion filters: a new filter structure based upon morphological opening and closing." In E. R. Dougherty, J. Astola, and H. Longbotham, eds., Nonlinear Image Processing IV. Proc. SPIE, v. 1902 (1993) pp. 106-115. (San Jose, California, Feb. 1-3, 1993.)

References for the MLV and MCV filters:

M. A. Schulze and Q. X. Wu. "Noise reduction in synthetic aperture radar imagery using a morphology-based nonlinear filter." Proceedings of DICTA95, Digital Image Computing: Techniques and Applications, pp. 661-666. (Brisbane, Australia, December 6-8, 1995.) The extended abstract and final published abstract for this paper are available.

M. A. Schulze and Q. X. Wu. "Nonlinear filtering for edge-preserving smoothing of synthetic aperture radar imagery." Proceedings of the New Zealand Image and Vision Computing '95 Workshop, pp. 65-70. (Christchurch, New Zealand, August 28-29, 1995.) The abstract for this paper is available.

Further Information

Please see my list of publications or contact me for further information about the MLV and MCV filters.

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Mark A. Schulze

Last Updated: 23 July 2003
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