Description: 用MATLAB对一图象分别用不同小波分解，观察高低频部分进行重构，比较重构误差，再进行阈值消噪，比较消噪前后图象。-MATLAB right one image with different wavelet decomposition, high-low-frequency observations for some remodeling, more reconstruction error and then de-noising, compared before and after image denoising. Platform: |
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Author:刘丽丽 |
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Description: 大多数图像去噪的方法,尤其是针对高斯白噪声的去噪方法,从本质上来说,都是低通滤波的方法.
低通滤波是一把双刃剑,在消除图像噪声的同时,也会消除图像部分有用的高频信息.因此,各种图像去
噪方法,其实就是在去噪和保留有用高频信息之间进行权衡-The majority of image denoising methods, especially for Gaussian white noise of the de-noising method, essentially, are low-pass filtering method. Low-pass filter is a double-edged sword, in the elimination of image noise at the same time, will be useful to eliminate some of the high frequency image information. Therefore, various image denoising methods, in fact, is useful in de-noising and retain high-frequency trade-off between information Platform: |
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Author:weiwei |
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Description: 图像去噪是图像处理领域中的一个重要内容，图像去噪总是需要在抑制噪声和保持图像细节之间做折衷。小波变换作为一种新的信号处理工具，在信号去噪领域已得到了成功的应用。在传统的基于正交小波变换的图像去噪方法中，重建图像在边缘附近容易产生振荡从而造成边缘失真，噪声较严重时还会产生模糊边缘；利用冗余小波变换，可以克服正交小波变换去噪存在的不足, 进一步提高算法的去噪性能-Image denoising image processing is an important area of content, image denoising is always the need to suppress noise and maintain a compromise between image detail. Wavelet transform as a new signal processing tools, in the field of signal de-noising has been applied successfully. In the traditional orthogonal wavelet transform based image denoising methods, the reconstructed image at the edge near the oscillation and thus prone to cause the edge of distortion, noise will also produce more serious when the fuzzy edge the use of redundant wavelet transform, orthogonal wavelet can be overcome Transform Denoising deficiencies, further improving the performance of denoising algorithms Platform: |
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Author:李胖子 |
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Description: 摘要 该文主要考虑利用图像噪声再生技术来提取图像细节 其思想是利用被滤除的噪声信号进行回收再利用 通过对噪声信号和初步去噪信号进行小波变换 比较它们的小波系数 当噪声信号的小波系数达到一定的阈值时 将噪声信号的小波系数保留叠加至初步去噪信号的小波系数 然后利用传统的软阈值去噪的方法来进行图像的去噪 从而达到既能够去除噪声 又能保留图像细节的目的 实验证明 该方法较传统的方法在去噪和细节保持上有改进-Abstract In this paper, consider using images to extract the noise regeneration of its ideological image detail is the use of the noise signal was filtered to recycle through the noise signal and the initial wavelet transform de-noising signal comparison of their wavelet coefficients of the wavelet signal when the noise coefficient reaches a certain threshold will be the noise signal superimposed to the wavelet coefficients to retain the initial de-noising signal wavelet coefficients and then using the traditional soft-threshold denoising approach to image denoising in order to achieve the removal of noise can not only be able to retain The purpose of image detail that the methods of the experiment a more traditional approach to denoising and detail in there to keep improving Platform: |
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Author:彭彭 |
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Description: 图片的灰度化和去噪程序，灰度化可画出直方图，去噪使用中值去噪和均值去噪，中值去噪可循环多次，导入要改包名。-And the gray-scale image denoising procedures, and can be painted gray histogram, the use of denoising Denoising and mean de-noising, in denoising can be recycled many times, we have to change package names to import. Platform: |
Size: 6144 |
Author:林岩峰 |
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Description: 生成一副服从正态分布且加入噪声图像，用于初始实验-Normal distribution to generate an image and adding noise to the initial experiments
搜索 Platform: |
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Author:娟娟 |
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Description: GCV阈值，在图像去噪上广泛应用，其值接近理想门限，去噪效果相当好，结果小波，更可以达到更佳的效果。-GCV threshold, widely applied in image denoising and its value is close to the ideal threshold, de-noising result was very good, the results of wavelet, but also can achieve better results. Platform: |
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Author:Jason |
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Description: 小波方法和偏微分方程方法是图像去噪中的主要方法。该文提出基于离散小波变换对图像进行阈值去噪，得出了小波阈值的偏微
分方程表示形式，在此基础上研究偏微分方程的解法，采用分数步的小波阈值方法对图像去噪，得到了较好的去噪效果，同时可以保护边
缘。数值试验结果表明，该方法具有比小波方法更好的去噪效果，能获得较高的信噪比-Wavelet method and partial differential equations is the main method of image denoising. In this paper, based on discrete wavelet transform image threshold denoising, wavelet threshold obtained indicated that the form of partial differential equations, in this study based on the solution of partial differential equations, using fractional steps of wavelet thresholding methods for image to noise, have been well de-noising effect at the same time can protect the edge. Numerical experimental results show that the method is better than the wavelet method for denoising results are able to obtain a higher signal to noise ratio Platform: |
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Author:MaxineChan |
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Description: 在小波
域图像去噪算法中，基于统计模型的去噪算法由于充分利用了已知的先验信息，取得较好的
去噪效果，是近来小波去噪领域研究的热点。本文着重研究小波系数的统计模型，并将其应
用于图像去噪和纹理分析中
-In the wavelet domain image denoising algorithm, de-noising algorithm based on statistical models known as take full advantage of a priori information, to obtain better denoising results of recent research in the field of wavelet denoising hot spots. This article focuses on studies of the statistical model of wavelet coefficients and applied to image denoising and texture analysis Platform: |
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Author:图像 |
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Description: 数字图像处理中的图像去噪部分，用低通去噪和non-local means两种方法，其中用non-local means，可把信噪比提高10dB左右。-Digital image processing, image denoising part of the low-pass de-noising and non-local means are two ways in which non-local means to signal to noise ratio increased by about 10dB. Platform: |
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Author:姚冠文 |
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Description: 对单幅雾天图像进行去噪的同时对其进行复原的计算机技术，对复杂天气对图像质量进行的影响进行了有效评估和分析，并对图像去噪技术和复原技术进行了具体描述，运用实际例子对本文提出的图像去噪和复原技术进行了论证实现。-For single image de-noising fog while its recovery computer technology, the impact of weather on the complexity of the image quality for the effective assessment and analysis, and image de-noising technology and recovery techniques are described in detail, using This paper presents a practical example for image denoising and restoration techniques were demonstrated to achieve. Platform: |
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Author:gdfg |
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Description: 我按这篇文章做的，广义高斯分布及其在图像去噪中的应用，没有完全做出来，谁做出来了，分享一下- The statistics of imagewavelet coefficients is non2Gaussian and can be described by generalized Gaussian
distribution (GGD). The paper investigates the issues of GGD statisticalmodel for wavelet coefficients in a sub2
band and the corresponding parameters estimation . A Bayesian estimate based subband adaptive thresholding de2
noising algorithm is designed, and the performance of noise reduction of this algorithm, compared with other clas2
sicalwavelet thresholding denoising methods, is discussed according to simulation results .
Keywords image wavelet coefficients generalized Gaussian distribution BayesShrink algorithm image de Platform: |
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Author:李胖子 |
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