ADAPTIVE MEDIAN FILTERS - NEW ALGORITHMS AND RESULTS

Based on two types of image models corrupted by impulse noise, we propose two new algorithms for adaptive median filters, These have variable window size for removal of impulses while preserving sharpness, The first one, called the ranked-order based adaptive median filter (RAMF), is based on a test for the presence of impulses in the center pixel itself followed by the test for the presence of residual impulses in the median filter output, The second one, called the impulse size based adaptive median filter (SAMP), is based on the detection of the size of the impulse noise. It is shown that the RAMF is superior to the nonlinear mean L(p) filter in removing positive and negative impulses while simultaneously preserving sharpness; the SAMF is superior to Lin's adaptive scheme because it is simpler and better performing in removing the high density of impulsive noise as well as nonimpulsive noise and in preserving fine details, Simulations on standard images confirm that these algorithms are superior to standard median filters.