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  • 标题:Noise Removal in Microarray Images Using Variational Mode Decomposition Technique
  • 本地全文:下载
  • 作者:G. Sai Chaitanya Kumar ; Reddi Kiran Kumar ; G. Apparao Naidu
  • 期刊名称:TELKOMNIKA (Telecommunication Computing Electronics and Control)
  • 印刷版ISSN:2302-9293
  • 出版年度:2017
  • 卷号:15
  • 期号:4
  • 页码:1750-1756
  • DOI:10.12928/telkomnika.v15i4.5375
  • 语种:English
  • 出版社:Universitas Ahmad Dahlan
  • 其他摘要:Microarray technology allows the simultaneous monitoring of thousands of genes in parallel. Based on the gene expression measurements, microarray technology have proven powerful in gene expression profiling for discovering new types of diseases and for predicting the type of a disease. Enhancement, Gridding, Segmentation and Intensity extraction are important steps in microarray image analysis. This paper presents a noise removal method in microarray images based on Variational Mode Decomposition (VMD). VMD is a signal processing method which decomposes any input signal into discrete number of sub-signals (called Variational Mode Functions) with each mode chosen to be its band width in spectral domain. First the noisy image is processed using 2-D VMD to produce 2-D VMFs. Then Discrete Wavelet Transform (DWT) thresholding technique is applied to each VMF for denoising. The denoised microarray image is reconstructed by the summation of VMFs. This method is named as 2-D VMD and DWT thresholding method. The proposed method is compared with DWT thresholding and BEMD and DWT thresholding methods. The qualitative and quantitative analysis shows that 2-D VMD and DWT thresholding method produces better noise removal than other two methods.
  • 关键词:empirical mode decomposition;variational mode decomposition;discrete wavelet transform;image enhancement;microarray images
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