A Robust Polynomial Filtering Framework for Mammographic Image Enhancement from Biomedical Sensors

This paper presents a non-linear framework employing a robust Polynomial filter for accomplishing enhancement of mammographic abnormalities outcoming from biomedical instrumentation, that is, X-rays instrumentation. The approach proposed in this work utilizes a linear combination of Type-0 and Type-II Polynomial filters as a generalized filtering solution to achieve enhancement of mammographic masses and calcifications irrespective of the nature of background tissues. A Type-0 filter provides contrast enhancement, suppressing the ill effects of background noise. On the other hand, Type-II filter performs edge enhancement leading to preservation of finer details. Contrast Improvement Index (CII) is used as a performance measure to quantify the degree of improvement in contrast of the region-of interest (ROI). In addition, estimation of signal-to-noise ratio (in terms of PSNR and ASNR) is carried out to account for the suppression in background noise levels and over-enhancements of the processed mammograms. These measures are used as a mechanism to optimally select the filter parameters and also serve as a quantifying platform to compare the performance of the proposed filter with other non-linear enhancement techniques to be used for diverse biomedical image sensors.