Wavelet transform based microarray image de-noising

dc.contributor.author	Patil, S.
dc.contributor.author	Naik, G.M.
dc.contributor.author	Pai, K.R.
dc.contributor.author	Gad, R.S.
dc.date.accessioned	2018-07-02T05:03:20Z
dc.date.available	2018-07-02T05:03:20Z
dc.date.issued	2017
dc.identifier.citation	International Journal of Emerging Technology and Advanced Engineering. 7(8); 2017; 137-139.	en_US
dc.identifier.uri	http://www.ijetae.com/files/Volume7Issue8/IJETAE_0817_19.pdf
dc.identifier.uri	http://irgu.unigoa.ac.in/drs/handle/unigoa/5282
dc.description.abstract	Accuracy of microarray gene expression based cancer classification depends on microarray image processing techniques. Image de-noising is one of the crucial step of the microarray image processing. Better the quality of microarray image, more accurate will be the result of cancer classification. In this paper, we have implemented Median filter and wavelet transform based filters with various thresholding techniques, to de-noise the microarray image. The performance of filters is compared using mean square error and peak signal to noise ratio.	en_US
dc.subject	Electronics	en_US
dc.title	Wavelet transform based microarray image de-noising	en_US
dc.type	Journal article	en_US