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
0 323
下载积分: 1 下载次数: 6
我要下载

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

  • PHD
    用PHD滤波的方法实现多目标跟踪，及对PHD滤波性能的检测。(PHD filter method using multi-target tracking, and performance testing for the PHD filter.)
    2021-01-01 18:48:58下载
    积分：1
  • dft
    图像的傅里叶变换。在代码中实现了将两幅图像的幅度谱和相位谱进行交换，进而理解两者在图像显示中的作用(Fourier transform of the image. Implemented in the code will be two images amplitude spectrum and phase spectrum of exchange, and thus to understand both the role of the image display)
    2011-05-09 19:28:41下载
    积分：1
  • src
    说明：  基于HLS的图像处理，opencv，可供软件人员使用(Image processing based on HLS)
    2020-12-31 21:39:37下载
    积分：1
  • Lab5.17-video_loopback_II_5146-4
    闻婷实验板的四通道视频采集实验，通过键盘控制四个通到采集图像，将采集的图像在同一台显示器上显示(Wen Ting experimental four-channel video capture board experiments, four-pass to collecting image, the collected image displayed on the same monitor keyboard control)
    2012-09-08 23:50:45下载
    积分：1
  • color-snake
    利用彩色蛇模型对彩色图像进行处理，即不将彩色图像分为Ｒ，Ｇ，Ｂ三个分量，而是将彩色图像视为单一簇的处理，反而会得到更好的边缘清晰度(The use of color snake model for color image processing, that is, not the color image into R, G, B three-component, but rather as a single cluster of color image processing, it will get better edge sharpness)
    2010-01-12 23:16:19下载
    积分：1
  • five-algorithm
    运用Soble,,Roberts算子,Prewitt算子,Log算子,Canny算子j进行边缘检测 (Using Sobel ,, Roberts operator, Prewitt operator, Log operator, Canny edge detection operator )
    2016-03-14 17:22:14下载
    积分：1
  • read_ENVIimagefile
    说明：  ENVI软件标准格式的高光谱遥感图像含有两部分：一个是高光谱图像 '*.img '，另一个是遥感图像头文件 '*.hdr'，该文件记录了遥感图像的信息，如图像尺寸、波段数、数据类型和大小端等。如果缺少头文件，将无法对遥感图像进行读取，因此头文件十分重要。 在Matlab中，将利用函数multibandread()对多波段（高光谱/多光谱）图像进行读取。(The hyperspectral remote sensing images of ENVI software standard format contain two parts: one is hyperspectral image'*.img ', the other is the remote sensing image header file'*.hdr', which records the information of remote sensing image, such as image size, band number, data type and size end, etc. If there is no header file, it will not be able to read remote sensing images, so header files are very important. In Matlab, multibandread () is used to read multiband (hyperspectral / multispectral) images.)
    2018-04-20 15:35:29下载
    积分：1
  • lyc_sst_monthly_gif
    说明：  基于MATLAB，对逐日的sst遥感数据做月平均并制作gif动图(Based on MATLAB, the daily SST remote sensing data are averaged monthly and the GIF map is made)
    2021-03-02 11:13:36下载
    积分：1
  • Khan2
    数字图像copy-move篡改检测。特征提取，相似块搜索(detection of copy-move forgery in digitial image)
    2011-09-10 11:45:06下载
    积分：1
  • SPIHT2
    根据paper思想，自己编写的SPIHT编解码。可以处理不同图像大小的小波系数，严格按照paper中的算法编写。细节见说明文档(under the paper thinking, their preparation SPIHT codec. Image can handle different sizes of the wavelet coefficients and strictly according to the paper prepared algorithm. For details, see the documentation)
    2007-04-18 11:41:46下载
    积分：1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载

热门标签

Visual C++ matlab C/C++ Java Others Unix_Linux EasyLanguage易语言 Visual Basic C# PDF C++ Delphi VHDL ASP WINDOWS
热门下载

Copyright© 2019-2026 | Powered by Imdn | 浙ICP备16007336号 | IMDN交流 | 联系客服（QQ：3324461878）

本网站资源收集自网络及网站用户上传，若有侵权请邮件至（3324461878@qq.com），核实后我们会在24小时内删除，谢谢！