An Improved Compressed Sensing Method for cDNA Miacorarray Image Denoising

摘要

Microarray image processing plays an important role among array analysis and its precision will affect the application of gene chip. However, real microarray images drawn from various experimental procedures may contain noises and other artifacts, which result in a lower image processing accuracy. Hence, in this paper, we propose a novel image denoising method by introducing the compressed sensing theory into microarray image noise reduction. To improve the matching pursuit efficiency, the correlation coefficient is adopted. Experiments on 17 simulated images and 59 real microarray images obtained from the DeRisi, SIB and BCM data sets are conducted. Qualitative and quantitative results compared with the Donoho threshold, generalized wavelet and adaptive thresholding algorithm, reveal that our proposed method performs better on reducing the noises.