Abstract
Digital. Mammography has. become the most effective. technique for. detecting the. early modalities. of breast. cancer. Noise is a major issue in mammogram images which has to be resolved for analysis of mammogram. Three conventional denoising methods such as mean, median and adaptive median filters are discussed in this paper. These techniques helps to find region of interests of mammogram images by enhancing the image quality, preserving the edges and removal of noise. For testing scenarios, Mammographic. Image. Analysis Society. (MIAS) database is. used in order to carry out the estimation of performance parameters in terms of Peak. to signal and noise ratio (PSNR), mean square. error. (MSE), signal and. noise ratio (SNR), root mean. square error (RMSE) of denoising images. In experimental results PSNR, SNR, MSE and RMSE average values are evaluated for test images. From those results, it is concluded that adaptive median filter has low noise as comparison to other two techniques as its PSNR value is high and MSE value is low.
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