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.
