An edge-preserving filter for imagery corrupted with multiplicative noise

In the segmentation of natural imagery, differentiation at feature boundari es is of crucial importance. The high-amplitude, multiplicative speckle noi se present in synthetic aperture radar (SAR) data demands a high level of f iltering, yet this noise must be removed without destroying the critical fe ature boundary information. We previously designed the minimum coefficient of variation (MCV) filter to meet the twin demands of noise removal and edg e preservation in SAR imagery. MCV-filtered images exhibit clear feature bo undaries, but the filter's strong edge-preserving nature also introduces st ep edge artifacts in areas of intensity gradient and texture. We present th e modified MCV filter (MMCV) which is able to significantly reduce the occu rrence of filtering artifacts, while retaining an edge-preserving character . The MMCV filter is compared to existing filters by operating them on SAR imagery and deriving edge maps from the filtered imagery. Though the MMCV-f iltered image is not the most visually pleasing, the linework derived from it is the most useful in terms of clean, continuous feature boundaries.