A modified unsharp masking with adaptive threshold and objectively defined amount based on saturation constraints

Unsharp Masking (UM) is a popular technique widely used for sharpening medical imagery. However, UM has two operational parameters which have crucial influence on its performance. They are amount (λ) and threshold (α). Improper selection of the threshold and amount will cause noise amplification and overshoot artefact, respectively. A fully adaptive UM with data driven operational parameters, for sharpening Magnetic Resonance (MR) images is proposed in this paper. The proposed sharpening scheme is compared with the homomorphic filter in terms of sharpness of the output image, width of salient edges, feature preservation, saturation and edge quality degradation due to noise. The proposed scheme of UM is found to be superior to homomorphic filter in terms of edge strength and feature preservation and it is free from overshoot artefacts. Modified configuration of UM, proposed in this paper can be used for improving the edge quality of MR images. It can be incorporated as a plug-in in software tools used for the automated analysis of MRI.