登录
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
0 350
下载积分: 1 下载次数: 6

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

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • contoulet-fusion
    基于contourlet的图像融合,低频分量在融合过程中使用加权平均的融合规则(Contourlet-based image fusion, the low frequency components in the integration process using the weighted average of the fusion rules)
    2011-11-16 16:38:15下载
    积分:1
  • key
    说明:  实现了基于关键像素点的FLICM图像分割算法,关键像素由局部最大值方法提取。(A FLICM image segmentation algorithm based on key pixels is implemented. Key pixels are extracted by local maximum method.)
    2020-06-25 09:20:01下载
    积分:1
  • 0034
    校正图像倾斜的程序,很好用,可以纠正几何投影变形(Image tilt correction procedures, very good use, you can correct the distortion geometric projection)
    2020-10-31 20:29:56下载
    积分:1
  • BP-classification
    BP神经网络图像分类程序,代码很好懂,适合初学者。样本选的不是很大。(BP neural network image classification procedures, code easy to understand for beginners. Sample selected is not great.)
    2013-07-24 18:19:51下载
    积分:1
  • 0987542
    说明:  一个声纹识别的全代码,包括语音信号的预处理,建模,和识别(Voiceprint identification of a full code, including the speech signal pre-processing, modeling, and identification)
    2009-08-06 15:52:39下载
    积分:1
  • harris
    harris算子寻找角点,并实现配准。附试验材料。(harris corner operator to find and to achieve registration. Test materials attached.)
    2008-12-18 20:56:20下载
    积分:1
  • RANSAC+SURF
    说明:  基于SURF算法实现图像特征提取与描述,使用RANSAC进行图像细配准(SURF algorithm was used to extract and describe image features, and RANSAC was used for image registration)
    2021-03-03 15:09:33下载
    积分:1
  • souhan_v32
    esprit算法对有干扰的信号频率进行估计,一种基于多文档得图像合并技术,搭建OFDM通信系统的框架。( esprit algorithm signal frequency interference can be assessed Based on multi-document image obtained combining technique, Build a framework OFDM communication system.)
    2017-04-28 19:14:03下载
    积分:1
  • PCA_Saliency_CVPR
    注意机制,显著图提取,使用PCA算法!效果理想。(Attention mechanism, saliency map extraction, using PCA algorithm! Effect ideal.)
    2016-04-17 23:48:52下载
    积分:1
  • lvboqi
    对图像进行模糊处理前的第一步设计操作,然后进行加强滤波处理(Fuzzy image processing operation prior to the first step in the design and then proceed to strengthen the filter processing)
    2008-12-29 15:10:12下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载