Noise Removal using Empirical Mode Decomposition and Wavelet Transform in Microarray Images

Abstract

A Deoxyribonucleic Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface, such as glass, plastic or silicon chip forming an array. The analysis of DNA microarray images allows the identification of gene expressions to draw biological conclusions for applications ranging from genetic profiling to diagnosis of cancer. The DNA microarray image analysis includes three tasks: gridding, segmentation and intensity extraction. In this paper, a method for noise removal in microarray image using Bidimensional Empirical Mode Decomposition (BEMD) is presented. The BEMD decomposes the image into IMFs and residual components. Then, the selected high frequency IMFs are de-noised with wavelet model and finally the BEMD reconstruction gives the de-noised image. The experimental results show the proposed algorithm can perform significantly better in terms of noise suppression and detail preservation in microarray images.