Image sifting for micro array image enhancement

Abstract

cDNA micro arrays are more and more frequently used in molecular biology as they can give insight into the relation of an organism's metabolism and its genome. The process of imaging a micro array sample can introduce a great deal of noise and bias into the data with higher variance than the original signal which may swamp the useful information. As imperfections and fabrication artifacts often impair our ability to measure accurately the quantities of interest in micro array images, image processing for analysis of these images is an important and challenging problem. How to eliminate the effect of the noise imposes a challenging problem in micro array analysis. In this paper we implemented a novel algorithm for image sifting which could remove objects with definite size from macro array images. We used regular moving grids to sift noise object and obtained clean images for segmentation. The results have been compared with SWT, DWT and wiener filter denoising. © Springer-Verlag Berlin Heidelberg 2007.