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机构地区:[1]成都信息工程大学,四川 成都
出 处:《图像与信号处理》2020年第2期119-128,共10页Journal of Image and Signal Processing
摘 要:近十几年来,随着科学技术的高速发展,小波变换作为一种数学分析工具,具有多尺度分辨特征,在许多工程应用领域已经取代传统的技术方法。本文首先介绍了关于小波变换的基本理论及相关图像去噪增强基本原理,结合地震图像及噪声特点,围绕小波分析法对地震图像去噪增强做了详细论述,采用了小波变换软、硬阈值方法,并对小波阈值函数进行相应的改进,再利用直方图均衡化提升图像对比度。经实验表明新阈值函数能够有效去除噪声,对地震图像去噪增强效果明显。In recent years, with the rapid development of science and technology, as a mathematical analysis tool, wavelet transform with multi-scale resolution features has replaced the role of the traditional technical methods in many engineering applications. This thesis first introduces the basic theory of wavelet transformation and the basic principle of the related image in de-noising and enhance-ment. Second, the thesis is combined with the characteristics of the seismic image and the noise, and the seismic image de-noising and enhancement are discussed in detail by wavelet analysis. The soft and hard threshold methods have been selected. And the threshold function of the wavelet has been bettered;then the histogram equalization is used to improve the image contrast. Finally, it is concluded that the new threshold function can effectively remove the noise and obviously en-hance the effect of the image de-noising.
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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