Statistical techniques for noise removal from visual images

Lloyd G. Allred; Gary E. Kelly

doi:10.1117/12.60572

1 July 1992 Statistical techniques for noise removal from visual images

Lloyd G. Allred, Gary E. Kelly

Proceedings Volume 1702, Hybrid Image and Signal Processing III; (1992) https://doi.org/10.1117/12.60572
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

The median operator has been demonstrated to be a very effective method for restoring recognizable images from very noisy image data. The power of the median operator stems from its non-algebraic formulation, which prevents erroneous data corrupting the final color computation. A principal drawback is that the median operator replaces all data, erroneous or not, the result being a net loss of information. This paper presents alternative statistical outlier techniques by which erroneous data is readily recognized, but valid data usually remains unchanged. The result is an effective noise removal algorithm with reduced loss of information.

Citation Download Citation

Lloyd G. Allred and Gary E. Kelly "Statistical techniques for noise removal from visual images", Proc. SPIE 1702, Hybrid Image and Signal Processing III, (1 July 1992); https://doi.org/10.1117/12.60572

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