Abstract

Microarray technology has transformed the field of genomic research by allowing the simultaneous profiling of thousands of genes. The microarray process is based entirely on the accurate extraction of quantitative information from images. Several types of noises are caused by the imperfection in generation of microarray images which affects accurate gene expression profiling. Spot recognition is difficult task as noise sources during image acquisition damages the image. Thus, Denoising is one of the major pre-processing steps in microarray image analysis. This paper presents an overview of some of the popular methods used to denoise microarray images both in spatial and frequency domain. The performance metrics used to measure the image quality after denoising is also discussed.