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Wavelet transform based image processing techniques in non-image data sets

机译：非图像数据集中基于小波变换的图像处理技术

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摘要

Certain image processing methods such as filter banks, wavelet packets, and multiresolution analysis have been extensively used for efficiently decomposing, de-noising, compressing and reconstructing images in recent years. While these methods have been applied primarily in images, their usefulness for decomposing and de-noising sets of measured data has not been thoroughly established yet. This paper will explore the potential of the application of image processing methods in non-image data sets. It is shown that filter banks can be potentially used to process and de-noise seismic data sets successfully. The idea is to treat a seismogram like a "conventional" image and extract certain features in a similar fashion to traditional image processing techniques. In this particular paper, the usage and application of wavelet bases will be explored.
机译：近年来，诸如滤波器组，小波包和多分辨率分析之类的某些图像处理方法已被广泛用于有效地对图像进行分解，消噪，压缩和重建。尽管这些方法主要应用于图像，但是它们对于分解和消除测量数据集的有用性尚未完全确定。本文将探讨在非图像数据集中应用图像处理方法的潜力。结果表明，滤波器组可以潜在地成功地处理和消除地震数据集的噪声。这个想法是将地震图视为“常规”图像，并以与传统图像处理技术类似的方式提取某些特征。在本文中，将探讨小波基的用法和应用。

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