Mammogram denoising by curvelet transform based on the information of neighbouring coefficients
Computer, Communication, Control and Information Technology（2015）
摘要
We present here an experimental work on mammogram denoising by the mathematical tool called the curvelet transform. The infiltration of noise in mammogram during the X-ray screening is a common and inevitable phenomenon. And such noise is normally reduced by the curvelet transform based on conventional thresholding strategy called the hard thresholding (HT). Therefore, the motive of this experimentation is to suggest an alternate but efficient mechanism of mammogram denoising by the same transform but with different algorithms purely based on the information of the neighbouring coefficients. It is found that the curvelet transform applied with the precept of surrounding curvelet coefficients is visually and statistically better than the conventional approach based on HT.
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关键词
cancer,curvelet transforms,diagnostic radiography,image denoising,mammography,medical image processing,ht-based curvelet transform,x-ray screening,alternative mammogram denoising mechanism,conventional thresholding strategy,curvelet transform-based mammogram denoising,efficient mammogram denoising mechanism,hard thresholding-based curvelet transform,mammogram noise infiltration,mammogram noise reduction,neighbouring coefficient information-based curvelet transform,surrounding curvelet coefficients,curvelet transform,block thresholding,fast fourier transform,hard thresholding,microcalcification,noise reduction,psnr,speckle
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