搜索资源列表
sharpen
- 数字图像处理中的平滑和锐化（边缘检测）。包括1、添加椒盐、高斯噪声。2对噪声污染的图像分别使用邻域平均法、中值滤波法、K邻近平均法进行平滑。3对一幅图像利用Roberts梯度法、Sobel算子和拉普拉斯算子进行锐化，并比较结果。附处理源图像和处理结果截图。 -Digital image processing smoothing and sharpening (edge detection). Including 1, add salt and pepper, Gaussian noise.
Gaussian-Noise-Image-Add
- 这个程序用于在图片中增加各种噪声，如高斯椒盐噪声, 加性或乘性等多种混合噪声，用于其它程序的测试。-This procedure is used to increase the variety of picture noise, such as salt and pepper Gaussian noise, additive or multiplicative noise, such as a mixture for testing other programs.
DBAIN.m
- DBAIN: 用DBA方法来去除高密度脉冲噪声，如椒盐噪声的去除-DBAIN: using DBA method to remove high-density impulse noise, such as salt and pepper noise removal
addnoise
- MATLAB 给图像添加各种噪声：如椒盐噪声，高斯噪声、乘性噪声等等。-MATLAB add all kinds of noise to the image: If salt and pepper noise, Gaussian noise, multiplicative noise and so on.
medianFilter
- 图像处理中的中值滤波源代码，能够较好的模糊图像，除去椒盐噪声。-Image processing median filter source code, be able to better fuzzy images, remove the salt and pepper noise.
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
NoiseReductionUsingaMedianFilter
- 本实验要求编写一个中值滤波的程序，并对产生的椒盐噪声的图像进行中值滤波处理。中值滤波是基于统计学的一种非线性滤波方法。我们还需要知道一个按大小排列的数组中间位置上的数据称为是中值。通过修改在实验project03-04的程序实现3*3中值滤波。-Prepared in this experiment, a median filtering process, and salt and pepper noise generated by the image processing median fil
noise-plus-image
- 对图像添加各种噪声 高斯噪声 淑盐噪声-Add a variety of image noise, Gaussian noise, noise, salt-sook
meanFilter
- Mean filter to get rid of salt and pepper noise in images using openCV library for VC-Mean filter to get rid of salt and pepper noise in images using openCV library for VC++
ImageNoiseReduction
- 均值滤波对高斯噪声的效果 二维自适应维纳滤波对高斯噪声的滤除效果 对加入椒盐噪声的图像分别作均值、中值和维纳滤波 分别使用二维统计滤波对椒盐噪声和高斯噪声进行滤波 利用wrcoef2函数进行图像去噪-Mean filter on the effect of Gaussian noise two-dimensional Adaptive Wiener filtering of the Gaussian noise filtering effect the image to j
imageprocessing
- 将lena图像（或别的）施加Pa=Pb=0.1的椒盐噪声，然后采用3 3中值滤波进行处理，给 出去噪前后的图像 将Pepper图像分别进行平滑和锐化处理，分别给出滤波后的图像-The lena image (or other) the imposition of Pa = Pb = 0.1 of the salt and pepper noise, then a 3 3 median filter processing, the image will be given before an
Matlab-image-add-noise-and-filtering
- Matlab图像增强实验源代码与图片展示，内有用matlab为图像增加椒盐噪声白噪声程序。再用平滑滤波与中值滤波对图像进行处理。-Matlab source code for image enhancement and image experiments show, the image in a useful increase in salt and pepper noise matlab white noise process. And then filtering and median fi
adding--salt-and-pepper-noise
- VC++下加入椒盐噪声，可以用于验证高斯，均值，中值滤波等方法效果-Add salt and pepper noise in VC++ condition, which can be used to verify the effect of Gaussian, mean, median filtering method.
Noise-estimation-in-wavelet-domain
- 对含噪声的图像进行识别和估计，通过小波分解，在频域中完成对图像的识别，判断是椒盐噪声还是高斯噪声，并对参数的值进行估计。-Identify and estimate noisy images, through the wavelet decomposition in the frequency domain to complete the image recognition to determine the salt and pepper noise or Gaussian noise, and
noise
- 在图像中增加噪声，可完成高斯噪声，椒盐噪声等集中噪声的添加-Increase in image noise, Gaussian noise can be completed, such as concentration of salt and pepper noise added noise
Add-SP-Noise-and-Median-Filter
- 本工程程序对lena施加Pa=Pb=0.1的椒盐噪声，然后采用3*3中值滤波处理，给出去噪前后的图像。-The engineering process for lena put Pa = Pb = 0.1 salt and pepper noise, then a 3* 3 median filtering, give the image before and after denoising.
noise
- 使用中值滤波器对加入噪声的图像进行滤波处理。噪声有均匀噪声、高斯噪声和椒盐噪声-Using the median filter. Noise with uniform noise, Gaussian noise and salt and pepper noise
adding-noise
- 这是一个噪声发生器的matlab源代码，包括椒盐噪声，高斯噪声-noise ganerator including gaussian and pepper noise
noise
- 1. 用 butterworth和理想低通滤波器对受椒盐噪声和高斯噪声污染的图像进行平滑处理, 计算平滑前后的PSNR(峰值信噪比). 2. 用 3x3邻域平均平滑和3x3中值滤波对受椒盐噪声和高斯噪声污染的图像进行平滑处理, 计算平滑前后的PSNR(峰值信噪比). 3. 用 roberts算子和Laplace算子对一图像进行锐化处理, 得到其边缘二值图像.-Salt and pepper noise and Gaussian noise images with butterworth
Salt-and-pepper-noise-filtering
- 椒盐噪声的维纳滤波，中值滤波以及均值滤波。是数字图像处理里面最要的图片噪声处理方法。-Salt and Pepper Noise Wiener Filtering, Median Filtering and Mean Filtering. Is the digital image processing inside the most important picture noise processing methods.