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Mammogram Images Enhancement using Adaptive Morphological Bilateral Filter

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Roa I. Suliman, Zeinab A. Mustafa, Banazier A. Ibraheem
10.5120/ijca2018916613

Roa I Suliman, Zeinab A Mustafa and Banazier A Ibraheem. Mammogram Images Enhancement using Adaptive Morphological Bilateral Filter. International Journal of Computer Applications 179(27):45-50, March 2018. BibTeX

@article{10.5120/ijca2018916613,
	author = {Roa I. Suliman and Zeinab A. Mustafa and Banazier A. Ibraheem},
	title = {Mammogram Images Enhancement using Adaptive Morphological Bilateral Filter},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2018},
	volume = {179},
	number = {27},
	month = {Mar},
	year = {2018},
	issn = {0975-8887},
	pages = {45-50},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume179/number27/29132-2018916613},
	doi = {10.5120/ijca2018916613},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Noise, poor image contrast, in homogeneity, weak boundaries and special marks existing in the mammogram images makes diagnosis procedure extremely difficult, so there are needs for a way to denoise those images while preserving their important features. The Adaptive bilateral filter sharpens an image by increasing the slope of the edges without producing overshoot or undershoot. Morphological operations such as dilation, erosion, opening and closing with appropriate structure element size are offering a quality Sharpening enhancement. The performance of the filter was improved by including the mathematical morphology operations along with adaptive bilateral filter process. The parameters of the Adaptive bilateral filter are optimized with an iterative algorithm. The proposed method was applied for mammogram images. The performance analysis of the filter with respective design parameters and metrics are compared with existed algorithm the results were judged by three metrics; mean square error (MSE), structure similarity index (SSIM) and peak signal to noise ratio (PSNR).

References

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Keywords

Adaptive bilateral filter, mammogram images, mathematical morphology, morphological opening, morphological closing, mean square error (MSE), peak signal to noise ratio (PSNR), structure similarity index (SSIM),