Abstract
As the aim of using microarray technology is to try to understand fundamental aspects of growth and development as well as to explore the underlying genetic causes of many human diseases, the restoration of the ideal microarray image’s properties in a noisy image, is an urgent priority of the image processing procedure. The scope of this work is to describe and evaluate different methodologies for noise reduction in microarray images. In this paper, two basic approaches to microarray image denoising: spatial filtering methods and transform domain filtering methods are presented. The image denoising, with spatial filtering techniques as well as hard and soft thresholding of wavelet coefficients have been tested in microarray images of gene expression profiles of human sarcoma using the Stanford MicroArray Database.Keywordsmicroarrayimage denoisingwaveletspatial filters
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