The following content of this thesis is about an analog receiver for MR spectrometer based on PCI bus and wavelet based MR image denoising method.
本文后面的内容将讨论核磁共振成像仪中的接收机的设计，以及数据后处理过程中的图像降噪方法。
In view of the welding image feature of strong noise and poor stability, a fuzzy detection algorithm of welding image based on wavelet and morphology denoising was presented.
针对焊接图像噪声大、稳定性差的特点，提出了一种基于小波降噪和形态学模糊检测的算法。
Image denoising experiments show that wavelet transform for image denoising is better than mean filtering, no significant difference compared with median filter.
图像的消噪实验表明，小波变换用于图像消噪效果优于均值滤波，与中值滤波去噪相比无明显差别。
Combined with the characteristics of seismic image noise, using multi-scale wavelet transform, presents a new adaptive wavelet threshold denoising algorithm.
结合地震图像噪声的特点，利用多尺度小波变换的优点，提出一种新的自适应小波阈值去噪算法。
A new locally adaptive image denoising method, which exploits the intra-scale and inter-scale dependency in the dual-tree complex wavelet domain, is presented.
充分利用二元树复数小波域内系数尺度间和尺度内的统计依赖关系，提出了一种新的局部自适应图像去噪方法。
This paper is mainly studied denoising of image. Denoising methods of image are introduced such as average method, morphological filtering, median filt ring and wavelet.
本文主要以图像除噪为研究对象，介绍了图像的降噪方法—平均值法、形态学滤波器、中值滤波器以及小波。
Using the features of wavelet transform that can save detail image information, an image denoising method with the combination of nonlinear diffusion and wavelet transform was presented.
利用小波变换能够很好地保留图像细节信息的特点，提出了一种将非线性扩散方程和小波变换相结合的图像去噪方法。
This article proposes to utilize the dual-tree complex wavelet transformation to the core image denoising, and good effect is obtained.
岩心图像的去噪是后续的目标检测与定量分析的关键。
The image denoising method is proposed based on dual tree complex wavelet transform, which can do better both in features preserving and noise removing.
将对偶树复小波变换应用于图像去噪，可以更好地表示图像的边缘和纹理特征，从而得到较小波更好的去噪效果。
Image is restored which is blurred by the known linear model and noise, with the method of frequency-domain regularized inversion and wavelet-domain wiener filter denoising.
采用频域正则化求逆和小波域维纳滤波去噪的方法对已知线性降晰模型的含噪图像进行图像复原。
The main contributions are summarized as follows:1. Proposed an integrated denoising algorithm based on mid-value filtering and wavelet transform of fingerprint image.
主要工作如下：1。提出了一种基于中值滤波与小波变换的指纹图像去噪方法。
And then addressing SAR image speckle denoising, this dissertation proposed a new method based on bivariate shrinkage function combined with enhancement of wavelet significant coefficients.
其次针对SAR图像相干斑抑制问题，提出一种双变量收缩函数与小波系数显著性增强相结合的SAR图像的斑点抑制算法。
Secondly, using locally variance estimation, a locally adaptive image-denoising algorithm was presented. Also this algorithm could be applied to the complex wavelet domain.
在实验中，将该算法分别应用到实值离散小波变换域和双树复数小波变换域，并和隐马尔科夫模型的去噪方法做了比较分析。
The third algorithm proposes a hybrid image denoising algorithm based on wavelet shrinkage and TV diffusion owing to the disadvantage of TV diffusion.
第三种算法根据全变差模型在去除噪声时的缺陷，提出了将非抽样小波和全变差模型结合起来的自适应混合去噪策略。
The third algorithm proposes a hybrid image denoising algorithm based on wavelet shrinkage and TV diffusion owing to the disadvantage of TV diffusion.
第三种算法根据全变差模型在去除噪声时的缺陷，提出了将非抽样小波和全变差模型结合起来的自适应混合去噪策略。
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