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如何在图像中加入某一固定snr的噪声?分类:matlab与图像处理
在利用matlab做一些自己算法的抗噪分析中,常常会遇到这个问题,matlab中的加噪函数是imnoise,里面的参数是噪声的均值,方差(高斯噪声)或者是感染概率(椒盐噪声),参数不能是snr值,但是很多国外的文章的噪声分析中都是用snr值来衡量加入噪声的程度的-how the image to a fixed snr noise? Categories : Matlab and image processing using
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分块有损压缩图像忽略了块间相关性,重构时会产生块效应,该文提出一种空域自适应去块效应算法。对块边缘采用方向自适应
有理滤波,以弱化块效应。根据块的内部活动性将图像块分成平坦块和纹理块2 类,利用基于方差的空域检测方法检测出平坦块,并对平
坦块进行邻块边缘自适应平滑。实验结果表明,该算法有效去除了块效应,一定程度上提高了信噪比,算法简单且鲁棒性较好。-Block lossy compression image ignores the inter-block correlation, Rec
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计算SENSE重建图像中的g-factor,这是并行磁共振成像SENSE算法的关键一步-G-factor is the metric to quantify the amplificaiton of noise power in reconstructing SENSE accelerated image. The detail was presented in Pruessmann s 1999 Magn. Reson. Med. paper. In theory, g-factor is t
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bmp图像数字处理;图像信息的统计:直方图,最大最小灰度,熵,方差,平均灰度;灰度变换:分段线性变换,阈值,直方图的均衡化;中值滤波(加噪声),梯度算子;数字卷积,增加一个过滤类;几何变换:旋转,几何校正
-bmp image digital processing image information of the statistics: histogram, max-min gray, entropy, variance, average gray gray-scale transfor
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Simulations over AWGN and Rayleigh channels, at various signal-to-noise ratios, verify the excellent performance of this novel APEL-turbo scheme. Performance comparisons were carried out between turbo coded APEL, JPEG, and BMP image files.
To provi
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最小邻域均值投影函数及其在眼睛定位算法.提出一种投影函数:最小邻域均值投影函数.该函数通过计算每条投影线上各像素点邻域均值的最小值
来跟踪图像中的低灰度特征.与传统的积分投影函数和方差投影函数相比,它以求最小值的局部选择性代替传统投
影函数的全局累加性,因此具有对片状噪声不敏感的特点、此外,在计算过程中,它还能记录最小值点的二维位置信
息,是一个二维的搜索算子、最小邻域均值投影函数的这些特点使其非常适合于眼睛定位.它对眼睛,特别是瞳孔,总
能够产生精确、鲁棒的响应通过在CAS—P
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Decompose image into subbands, denoise, and recompose again.
fh = decomp_reconst(im,Nsc,Nor,block,noise,parent,covariance,optim,sig)
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (opti
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Decompose image into subbands, denoise using BLS-GSM method, and recompose again.
fh = decomp_reconst(im,Nsc,filter,block,noise,parent,covariance,optim,sig)
im: image
Nsc: number of scales
filter: type of filter used (see namedFilt
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Abstract—The fingerprint segmentation algorithm based on gray
variance can t segment those fingerprint images with high noise.
After analyzing limitation of the fingerprint image segmentation
algorithm based on gray variance, the paper proposes
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在图像中添加高斯噪声,必须详细地说明噪声均值和方差。-Add Gaussian noise in the image must detail the noise mean and variance.
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Total Variation Denoising-TV denoising (scalar fidelity term) [ROF92]
Reduces the total-variation of the image. Filters out noise while preserving edges. Textures and fine-scale details are also removed. In this demo the assumption is that a white
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BMP图像处理程序,包括模拟信道产生的高斯加性噪声;图像灰度变换;图像的拉普拉斯边缘提取;中点滤波法的debluring;图像线性模糊。
图形显示函数,包括DDA方法画直线;中点裁剪法;liang-barsky算法的窗口裁剪;种子填充算法;
随机信号处理程序,包括产生正态分布、均匀分布样本;计算其均值与方差;各样本的概率分布直方图分析;功率谱分析;样本叠加的PSD分布分析。-BMP image processing procedures, including analog channel
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本实验开发一个通用程序, 用在后续的几个实验中。(a) 编写一个给图像中添加高斯噪声的程序,程序的输入参数为噪声的均值与方差。
(b) 编写一个给图像中添加椒盐噪声的程序,程序的输入参数为两个噪声分量的概率值。
-In this study, the development of a common procedure, used in the follow-up of several experiments. (A) preparing a program to add Gauss
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matlab自动编程求取图像的峰值信噪比和方差-matlab automatically programmed to strike the image peak signal-to-noise ratio and variance
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对图像进行斑点噪声的添加,用方程f=f+n*f将乘性噪音添加到到图像f上,其中n是均值为零,方差为var的均匀分布的随机噪声。
-Image spots of noise, multiplicative noise is added to the equation f = f+n* f to the image f, where n is zero mean, variance var, uniformly distributed random noise.
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本实验要求开发一个通用程序,即要求编写一个给图像中添加高斯噪声和椒盐噪声的程序,添加高斯噪声的程序输入参数为噪声的均值和方差,添加椒盐噪声程序的输入参数为两个噪声分量的概率值。-This experiment requires the development of a common program, that is required to write a program to add Gaussian noise and salt and pepper noise to the image, a
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Denoising
Reduces the total-variation of the image. Filters out noise while preserving edges. Textures and fine-scale details are also removed. In this demo the assumption is that a white Gaussian noise is added with a-priori known (or estimated) n
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Denoising
Reduces the total-variation of the image. Filters out noise while preserving edges. Textures and fine-scale details are also removed. In this demo the assumption is that a white Gaussian noise is added with priori known (or estimated) noi
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使用MATLAB GUI用户界面实现对打开的图像进行直方图均衡化,加噪(设置均值和方差),旋转(设置旋转角度)并保存。-MATLAB GUI user interface to open image histogram equalization, plus noise (set the mean and variance), rotation (to set the rotation angle) and save.
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由于光线分布不均匀或斑块噪音干扰等原因,往往使所要处理的指纹的灰
度值分布缺乏均匀性。在指纹特征自动识别提取过程中,造成许多传统的算法在局部出
现很大的误差。利用方差和均值特征的自动提取方法,首次对不均匀灰度图像进行自适
应分割。然后通过对图像分区域进行不同程度的自适应调整,使具有相同属性的像素单
元具有近似的灰度值分布。调整结果的灰度均匀水平与预先指定的调整精度成正比。这
种调整不仅提高了图像分割的自适应性,而且进一步扩大了一般阈值算法的应用领域。-Gray value d
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