alexa Abstract | A Study On Preprocessing A Mammogram Image Using Adaptive Median Filter
ISSN ONLINE(2319-8753)PRINT(2347-6710)

International Journal of Innovative Research in Science, Engineering and Technology
Open Access

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Research Article Open Access

Abstract

Digital mammogram becomes the most effective technique for early breast cancer detection modality and processing these images requires high computational capabilities. Computer image processing techniques will be applied to enhance images. This paper attempts to study about pre-processing is the most important step in the mammogram analysis due to poor captured mammogram image quality. Pre-processing is very important to correct and adjust the mammogram image for further study and processing. Different types of filtering techniques are available for pre-processing. Filters are used to improve image quality, remove the noise, preserves the edges within an image, enhance and smoothen the image. The experimental results concludes that the adaptive median filter is best for mammogram image noise removal and gives better performance by estimating the PSNR values

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Author(s): Dr.K.Meenakshi Sundaram , D.Sasikala , P.Aarthi Rani

Keywords

Digital mammogram becomes the most effective technique for early breast cancer detection modality and processing these images requires high computational capabilities. Computer image processing techniques will be applied to enhance images. This paper attempts to study about pre-processing is the most important step in the mammogram analysis due to poor captured mammogram image quality. Pre-processing is very important to correct and adjust the mammogram image for further study and processing. Different types of filtering techniques are available for pre-processing. Filters are used to improve image quality, remove the noise, preserves the edges within an image, enhance and smoothen the image. The experimental results concludes that the adaptive median filter is best for mammogram image noise removal and gives better performance by estimating the PSNR values, Otitis Media

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