The original image was part of a transverse MRI scan of a normal human brain and the median filter was used as a reference. The training window was located towards the upper left of the image and the MAE was evaluated after one or two applications. Both median and stack filters are effective, the main difference being that strong edges are retained in the twice-applied stack filter. Figure 5 shows MAE for median and stack filters. Data for the first application of filters of two sizes are presented in figure 6.
Execution time is proportional to the both.
The training window size was reduced with the affect on local and global MAE shown in figure 7. Whilst the smallest window produces a filter with good performance on itself, its effect on the full image is poor. Our approach also designs the filter on typical noise, then applies it to an unknown image. The alternative approach of using a phantom as the training object was rejected because of difficulty in achieving a precise match to geometric truth. We will not present results based on the MAE because of the absence of ground-truth, instead we examine a typical nuclear medicine bone scan, before and after filtering by a 13 point stack filter, figure 9a, left and right image respectively.