Performance measures for rank order filters

When evaluating the quality of rank order filtered images, quantitative measures like the mean absolute error (MAE) criterion have been used only with caution because they do not always agree with the results of subjective tests. In general, a large part of the error in a median filtered image falls into one of two categories: remaining impulses or edge smearing. It is known that the human eye responds differently to these two components, whereas measures like the MAE do not distinguish between them. The authors have decomposed the error components, and by computing the MAE separately for each, have found a pair of perceptually significant error measures.<<ETX>>

[1]  B I Justusson,et al.  Median Filtering: Statistical Properties , 1981 .

[2]  Lale Akarun,et al.  Adaptive decimated median filtering , 1992, Pattern Recognit. Lett..

[3]  B. Prasada,et al.  Adaptive quantization of picture signals using spatial masking , 1977, Proceedings of the IEEE.

[4]  Moncef Gabbouj,et al.  Optimal stack filtering and the estimation and structural approaches to image processing , 1989, Sixth Multidimensional Signal Processing Workshop,.