Second Moment Image Processing (SMIP)
The class of SMIP-algorithms (Second Moment Image Processing) is presented, containing some forms of adaptive unsharp masking as well as approximations of adaptive histogram equalisation. SMIP-algorithms allow to drive the image-processing parameters by means of the mean and the standard deviation of the pixels in a continuously sliding window. The clipping technique as originally proposed by Pizer can be reformulated more generally for use in specific variants of this class. SMIP is especially suited for processing large images where the number of operations per pixel must be kept as small as possible. These algorithms lend themselves to fast software as well as hardware implementations.
KeywordsFast Implementation Local Histogram Unsharp Masking Cumulative Histogram Adaptive Histogram Equalisation
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