Based Adaptive Wavelet Hidden Markov Tree for Microarray Image Enhancement
The accuracy of the gene expression depends on Microarray image processing technology. However, eliminating the noise from different sources inherented in the DNA microarray still a challenging problem, which mainly contribute to the diversity and complexity of the noise of Microarray image. Traditionally, statistical methods are used to estimate the noises of the microarray images. In this paper, we construct the adaptive tensor wavelets for microarray image denoising in terms of an explicit parameterizations of the univariate orthogonal scaling functions. The constructed adaptive wavelet keep the edge information as possible as. Combining our constructed adaptive wavelet and hidden markov tree model, we present a novel image denoising method, which shows the significant improvement for microarray image denoising through the concrete numerical experiments.
hidden Markov tree adaptive wavelet microarray images denoising
Li Ying Cui Li
College of Computer Science and Technology Jilin University Changchun 130012, China School of Mathematics Sciences Beijing Normal University Beijing 100875
国际会议
上海
英文
314-317
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）