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advanceCimage2
- 很多高级一点的图形图像处理程序，对图像进行傅立叶变换处理（图像变换）,进行高斯模糊处理（图像复原）,加入随机噪声,基于C＋＋开发，希望大家能用得着（－－）-many senior point graphics processing images on Fourier transform (Image Transform), Gaussian fuzzy processing (Image Restoration), by adding random noise, based on C + + d
gaussnoise
- 在图像中加入随机高斯噪声的源代码，在MATLAB环境下实现。-in the image by adding Gaussian random noise source code in the MATLAB environment to achieve.
matlabpro2
- 以matlab实现数字水印的生成和提取，用的是高斯随机序列生成的易碎的隐式数字水印。-to Matlab digital watermark generation and extraction, using a Gaussian random sequence generation of friable implicit digital watermarking.
GauNoise
- 高斯随机噪音程序，做理论模型数据时，一般会加高斯随机噪音，以模拟实际数据
imnoise2
- 产生均匀、高斯、椒盐、对数正态、瑞利、指数、厄兰随机噪声-Have a uniform, Gaussian, salt and pepper, Lognormal, Rayleigh, exponential, beijerland random noise
project1
- 可添加随机噪声、高斯噪声、椒盐噪声，并比较几种去噪算法的峰值信噪比-Can add random noise, Gaussian noise, salt and pepper noise, and compare several denoising algorithm PSNR
NoiseGenerator
- 本实验要求根据课本中给出的高斯噪声和椒盐噪声的概率分布的形状和参数编写两个通用程序分别给一个图像中添加高斯噪声和椒盐噪声。高斯噪声是n维分布都服从高斯分布的噪声，椒盐噪声是图像中经常见到的一种噪声是一种随机的黑点或者白点。在实验中通过它们对应的概率密度函数得到噪声分布函数进而与原图像进行叠加产生出对应的噪声图像-Textbooks in this experiment are given under the Gaussian noise and salt and pepper noise in
restoration
- （1） 先由原始图像（任选）产生待恢复的图像；(产生方法如下：冲激函数为 ，将原始图像与冲激函数卷积产生模糊，然后再迭加均值为0，方差为8，16，32的高斯随机噪声而得到一组待恢复的图像。分别用逆滤波和维纳滤波恢复模糊后的图像。-(1) The first be the original image (optional) produces the image to be restored (generated as follows: impulse function, the original
Wavelet_IRLS
- 压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为ILRS算法，对256*256的lena图处理，比较原图和IRLS算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间-Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix
Wavelet_OMP
- 压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为OMP算法，对256*256的lena图处理，比较原图和OMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix
Wavelet_SP
- 压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为SP算法，对256*256的lena图处理，比较原图和SP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间-Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix and
Wavelet_ROMP
- 压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为ROMP算法，对256*256的lena图处理，比较原图和ROMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matr
Wavelet_SL0
- 压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为SL0算法，对256*256的lena图处理，比较原图和SL0算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间 -Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix
[kimi]Noise
- 实现了在图像中生成均匀随机噪声、高斯随机噪声和椒盐随机噪声的算法。-The code for creating uniform noise, Gaussian noise and Salt-pepper noise in image processing.
DCT_Gaosi_fenkuai
- 对256*256大小的8bit灰度lena图像进行仿真 将图像分为16*16的分块进行计算 稀疏矩阵采用DCT矩阵，观测矩阵采用高斯随机矩阵，重构采用OMP算法- 256* 256 size lena image simulation 8bit grayscale image is divided into 16 * 16 calculate block sparse matrix using DCT matrix, observation matrix using Ga
demo
- 将一副图像进行压缩并重现，使用dct测量矩阵，高斯随机矩阵，omp恢复算法-A pair of images were compressed and reproduce, using DCT measurement matrix, Gauss random matrix, OMP recovery algorithm
compressing
- 应用傅立叶变换矩阵对信号进行稀疏,经高斯随机观测矩阵观测,经正交匹配追踪算法重构.压缩感知入门程序-The Fourier transform matrix is used to spill the signal. Observed by Gaussian random observation matrix and reconstructed by orthogonal matching tracing algorithm. Compression Sensing Getting Started
zaosheng
- 对图像分别加入高斯噪声和随机噪声，再分别用中值滤波和邻域平均方法进行滤波(The Gauss noise and random noise are added to the image, and the median filtering and neighborhood averaging are used to filter the image respectively)
uvineanq
- 以matlab实现数字水印的生成和提取,用的是高斯随机序列(With matlab the generation and extraction of digital watermarking, using a gaussian random sequences)
cs
- 该文包含了压缩感知图像重构算法，有omp,cosamp,sp,可以选择观测矩阵高斯随机矩阵，稀疏随机矩阵，部分哈达码矩阵。(This paper includes compressed sensing image reconstruction algorithm. It has OMP, CoSaMP and sp. It can choose observation matrix Gauss random matrix, sparse random matrix and partial Had