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Microarray Image Denoising using Spatial Filtering and Wavelet Transformation

机译:使用空间滤波和小波变换的微阵列图像去噪

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As the aim of using microarray teclmology is to try to understand fundamental aspects of growth and development as well as to explore the underlying genetic causes of many human diseases, the restoration of the ideal microarray image's properties in a noisy image, is an urgent priority of the image processing procedure. The scope of this work is to describe and evaluate different methodologies for noise reduction in microarray images. In this paper, two basic approaches to microarray image denoising: spatial filtering methods and transform domain filtering methods are presented. The image denoising, with spatial filtering techniques as well as hard and soft thresholding of wavelet coefficients have been tested in microarray images of gene expression profiles of human sarcoma using the Stanford MicroArray Database.
机译:由于使用微阵列Teclmology的目的是试图了解增长和发展的基本方面,以及探讨许多人类疾病的潜在遗传原因,恢复理想的微阵列图像在嘈杂的形象中的性质,是一种紧急优先事项图像处理过程。这项工作的范围是描述和评估微阵列图像中的降噪方法。本文介绍了微阵列图像去噪的两种基本方法:出现了空间滤波方法和变换域滤波方法。使用STANFORD MICRARRAY数据库在人类肉瘤的基因表达谱的微阵列图像中测试了具有空间过滤技术的图像去噪以及小波系数的硬阈值和软阈值。

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