Mammogram Enhancement Using Quadratic Adaptive Volterra Filter- a Comparative Analysis in Spatial and Frequency Domain

Early breast cancer in women can be detected efficiently, by processing Mammograms in an effective way. Mammographic images are affected by noise which has low contrast and poor radiographic resolution based on illperformance of X-ray hardware systems. This leads to improper visualization of lesion detail. Generally Non-linear filters are preferred for image enhancement applications. Because they provide better filtering results not only by suppressing background noise but also preserving the edges. In this paper, an Adaptive Volterra filter is used for contrast enhancement of mammograms. A mammogram image which is affected by three types of noise individually like Gaussian, poison, white noise is considered. These noise elimination are done using adaptive Volterra filter and the performance of adaptive Volterra filter is compared with other spatial nonlinear filters like mean, median, min, max filters. The noisy mammogram is enhanced with five different filters in frequency domain which includes Volterra, Median, Min, Max, Mean filters. The comparison between spatial and frequency domain enhancement is done using five different filters with three types of noises. The performance measures like Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are computed and presented in this paper.