Switching median filter with a local entropy control

This paper presents a new switching median filter utilising local contrast entropy of the samples inside the filtering window. The proposed method is fully adaptive, it requires no optimisation and eliminates the main disadvantages of the local contrast probability based switching median. Excellent performance of the proposed method is a result of the successful analysis of input samples, as the local contrast entropy concept is able to efficiently differentiate between outliers and desired edge samples.

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