A Qualitative Approach on De-Noising and Segmentation Algorithms for Melanoma Images

In de-noising, better results are obtained by median filter in terms of the performance metrics like MSE and PSNR, whereas in segmentation algorithms sub-band thresholding algorithm gives better results in terms of minimum number of pixels. [...]it is necessary to remove the noise (de-noising) for b...

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Bibliographic Details
Published inAnnals of the Romanian society for cell biology Vol. 25; no. 2; pp. 1384 - 1393
Main Authors Lakshmi, B Vasantha, Sridevi, K
Format Journal Article
LanguageEnglish
Published Arad "Vasile Goldis" Western University Arad, Romania 01.01.2021
Subjects
Algorithms
Business metrics
Cellular biology
Decomposition
Fault diagnosis
Image processing
Melanoma
Methods
Mortality
Noise
Segmentation
Skin cancer
Wavelet transforms
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Summary:In de-noising, better results are obtained by median filter in terms of the performance metrics like MSE and PSNR, whereas in segmentation algorithms sub-band thresholding algorithm gives better results in terms of minimum number of pixels. [...]it is necessary to remove the noise (de-noising) for better quality of image. In this paper, we de-noise the melanoma skin cancer images from salt and pepper noise (20% noise density) and Gaussian noise (with zero mean, 0.01 variance) by using Wiener filter and median filter in filtering techniques whereas de-noising by soft thresholding algorithm in transform technique. [...]two-level decomposition requires one 2-D scaling function and three 2-D shifting functions.
ISSN:2067-3019
2067-8282