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首页 » Python » 基于深度卷积神经网络图像去噪算法

基于深度卷积神经网络图像去噪算法

于 2020-10-15 发布
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下载积分: 1 下载次数: 6
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代码说明：

说明：  用于图像去噪处理，使用ADM方法图像去噪处理器处理(Used for image denoising processing, using adm method image denoising processor processing)

文件列表：

DnCNN-Denoise-Gaussian-noise-TensorFlow-master, 0 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\DnCNN.py, 2950 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES, 0 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\denoised1.jpg, 9243 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\denoised2.jpg, 6945 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\denoised3.jpg, 9026 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\denoised4.jpg, 11065 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\denoised5.jpg, 11102 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\denoised6.jpg, 9139 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\denoised7.jpg, 10044 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\method.jpg, 39256 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\noised1.jpg, 20627 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\noised2.jpg, 17248 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\noised3.jpg, 18682 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\noised4.jpg, 20420 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\noised5.jpg, 19110 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\noised6.jpg, 20174 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\IMAGES\noised7.jpg, 21734 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\LICENSE, 1067 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\README.md, 3367 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet, 0 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\01.png, 38267 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\02.png, 34985 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\03.png, 40181 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\04.png, 42947 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\05.png, 40728 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\06.png, 40985 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\07.png, 39804 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\08.png, 151065 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\09.png, 185727 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\10.png, 177762 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\11.png, 209817 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TestingSet\12.png, 193637 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingResults, 0 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingResults\0_1440.jpg, 1847 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingResults\0_1520.jpg, 1830 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingResults\0_1600.jpg, 2277 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet, 0 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_17.jpg, 674 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_18.jpg, 619 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_19.jpg, 648 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_20.jpg, 579 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_25.jpg, 665 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_26.jpg, 677 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_27.jpg, 640 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\TrainingSet\1_28.jpg, 611 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\config.py, 106 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\network.py, 557 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\ops.py, 4376 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\save_para, 0 , 2019-03-02
DnCNN-Denoise-Gaussian-noise-TensorFlow-master\save_para\READMEN.txt, 30 , 2019-03-02

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发表评论

0 个回复

  • Extracted-the-circular
    二值化图像,提取图像中的圆形，例如提取照片中的车轮(Extracting a circular image, for example, extraction wheel photo)
    2014-05-17 11:34:12下载
    积分：1
  • HW2_code
    颜色和纹理特征的图像分割 颜色和纹理特征的图像分割(Image Segmentation Based on Color and Texture Features)
    2020-12-10 23:59:18下载
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  • GEI
    求质心到图像轮廓边缘的距离，并将其用figure表示出来(The distance from the center of mass to the edge of the image contour)
    2021-03-22 10:59:17下载
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    视频图像处理，采用三帧差分法进行视频前景和背景的分离(Video image processing, inter-frame difference method of separating the foreground and background video)
    2014-11-02 14:17:56下载
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  • waveletsfusion
    基于小波变换的图像融合源程序，通过调试，能直接使用。(Image fusion based on wavelet transform source code through the debugger can be used directly.)
    2009-10-23 17:28:44下载
    积分：1
  • Total-variation-image-deconvolution(dhxu757)
    一套使用全变分方法进行图像去噪处理的图像源代码(MATLAB),算法结果性能优良,适用范围广泛.(Use a variational method for image denoising images deal with the source code (MATLAB), the results of algorithm performance, the broad scope of application.)
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    图像处理的简单程序，适合初学者，自己好好看看(Simple image processing procedures, suitable for beginners, its a good look)
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    彩色位图转黑白位图代码。何东健《数字图像处理》随书光盘提供的源码。(color bitmap to black-and-white bitmap code. Dong- Jian "Digital Image Processing" With the CD source.)
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  • 一种基于改进的萤火虫算法(FA)优化二维Otsu图像分割算法(FA-2-Otsu)
    说明：  针对一维最大类间方差算法(1-Otsu)抗噪性能较低、二维最大类间方差算法(2-Otsu)计算复杂度高、实时性差的问题,提出一种基于改进的萤火虫算法(FA)优化二维Otsu图像分割算法(FA-2-Otsu).(In order to solve the problems of low anti noise performance of 1-otsu, high computational complexity and poor real-time performance of 2-otsu, an improved firefly algorithm (FA) is proposed to optimize the 2-otsu image segmentation algorithm (fa-2-otsu).)
    2019-12-23 21:45:50下载
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