Volume & Issue no: Volume 8, Issue 5, September - October 2019
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Title: |
Image Enhancement Based on Contextual Thresholding
Segmentation on Various Noise Deduction in
Mammogram Images |
Author Name: |
M Punitha, K Perumal |
Abstract: |
Abstract: Due to deficient performance of X-ray on
mammographic images are generally noisy with poor
radiographic resolution. This leads to improper visualization of
lesion details. The Image enhancement techniques are
important for visual inspection. In this paper the combined
features of enhancement technique and contextual thresholding
method for segmentation with Adaptive volterra filters are
usedto minimizing the effect of noises in the mammogram
images. After the process of de-noising, the enhanced results
will be segmented. Then we calculate the extracted tumor
portions and it has been compared by the various quality metrics
as Mean Square Error (MSE), Peak Signal to Noise Ratio
(PSNR), Mean Absolute Error (MAE) and Root Relative
Squared Error (RRSE) etc...This enhanced de-noising technique
is used to tested more images and the performance evaluated
based on their MSE and PSNR.The proposed enhanced denoising
technique gives better result than existing de-noising
technique.
Keywords: Mammogram Images, De-noising,
enhancement technique, Adaptive Volterra filter (AVF). |
Cite this article: |
M Punitha, K Perumal , "
Image Enhancement Based on Contextual Thresholding
Segmentation on Various Noise Deduction in
Mammogram Images" , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS) ,
Volume 8, Issue 5, September - October 2019 , pp.
001-005 , ISSN 2278-6856.
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