Soft, Hard and Block Thresholding Techniques for Denoising of Mammogram Images
Manas Saha, Mrinal Kanti Naskar, Biswa Nath Chatterji · IETE Journal of Research · 2015
Mammogram is an easy and affordable means of diagnosis of breast cancer. Like other medical data, it is also affected by noise during acquisition. Therefore, it is a challenge for the researchers to denoise the mammograms for clear data extraction. This paper aims at denoising the mammogram by the wavelet and the curvelet transform with a motive to investigate the role of the “embedded” thresholding algorithm. As the thresholding technique is a key factor for the noise reduction, a comprehensive study on the employment of the different types of the thresholding techniques with the transforms have been presented methodically. A standard mammogram from the Mammographic Image Analysis Society database is supplemented with different types of noise and then denoised by the wavelet and the curvelet transforms using the three commonly used thresholding techniques to compare the denoising performance of the thresholding algorithms along with the transforms. This investigation renders a clear insight to the selection of the thresholding technique while denoising the mammogram with the transform.