Microarray image de-noising using stationary wavelet transform

Presents a stationary wavelet transform (SWT) method to de-noise microarray images. It is well known that SWT is time invariant. Hence it is particularly important in statistical signal processing applications, such as signal detection and de-noising. The testing result on a sample microarray image has shown that a clear and a better resolution image is obtained using this method.

[1]  Hervé Carfantan,et al.  Time-invariant orthonormal wavelet representations , 1996, IEEE Trans. Signal Process..

[2]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[3]  S. P. Fodor,et al.  Light-directed, spatially addressable parallel chemical synthesis. , 1991, Science.

[4]  E. Southern.  Detection of specific sequences among DNA fragments separated by gel electrophoresis. , 1975, Journal of molecular biology.

[5]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[6]  B. Silverman,et al.  The Stationary Wavelet Transform and some Statistical Applications , 1995 .

[7]  E. Lander.  Array of hope , 1999, Nature Genetics.

[8]  Matthew A. Zapala,et al.  Software and methods for oligonucleotide and cDNA array data analysis , 2002, Genome Biology.

[9]  Jörg Rahnenführer,et al.  Unsupervised technique for robust target separation and analysis of DNA microarray spots through adaptive pixel clustering , 2002, Bioinform..

[10]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  Ronald W. Davis,et al.  Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray , 1995, Science.

[12]  Terence P. Speed,et al.  Comparison of Methods for Image Analysis on cDNA Microarray Data , 2002 .

[13]  Ajay N. Jain,et al.  Fully automatic quantification of microarray image data. , 2002, Genome research.

[14]  Yves Meyer.  Wavelets - algorithms & applications , 1993 .

[15]  Martin Vetterli,et al.  Adaptive wavelet thresholding for image denoising and compression , 2000, IEEE Trans. Image Process..