Description: Adopt mean value wave filtering way to dislodge noise to the image-Adopt mean value wave filtering way to disl odge noise to the image Platform: |
Size: 2600 |
Author:xue |
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Description: 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 Matlab to do some of his own anti-noise algorithm analysis, will often encounter this problem, which Matlab the noise function is imnoise. inside the parameters of the noise mean and variance (Gaussian noise) or the probability of infection (Impulse Noise) Parameter values can not be snr, But many foreign article noise analysis is used to measure the value snr joined the extent of noise Platform: |
Size: 2048 |
Author:顶替 |
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Description: Adopt mean value wave filtering way to dislodge noise to the image-Adopt mean value wave filtering way to disl odge noise to the image Platform: |
Size: 2048 |
Author:xue |
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Description: 本程序利用奇异值分解对3通道彩色图像进行压缩分解，具体步骤如下：
压缩过程：
1. 选取子图像大小K值，把图像分解成M×M个子图像，IMG(s),s=1,2,…, M2，其中M=N/K，原始图像IMG大小为N×N。
2. 计算这M2个子图像的平均值average，对每幅子图像减去均值图像得到新图像。
3. 计算相关矩阵R，其元素定义为 。
4. 计算R的特征值与特征向量，计算每幅子图像与最大特征向量的内积，便得到编码，即压缩后的图像。
-This procedure using singular value decomposition of 3-channel color image compression decomposition, concrete steps are as follows: compression process: 1. Select the sub-image size K value, the image is decomposed into M × M sub-image, IMG (s), s = 1, 2, ..., M2, in which M = N/K, the original image IMG size N × N. 2. M2 calculate the average of sub-image average, for each sub-image minus the new images mean images. 3. Calculation of correlation matrix R, defined as its elements. 4. Calculation of the characteristics of R value and eigenvector calculated each sub-image with the largest eigenvector of the inner product, they will have to code, that is, the compressed images. Platform: |
Size: 334848 |
Author:wangweiming |
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Description: 在VS.net2003下编译的，用了OpenCV开发库函数，包括bmp、jpeg格式图像的显示和存储，图像处理包括KNN均值，KNN中值，傅立叶变换，图像分割。-In the next VS.net2003 compiled using the OpenCV library function development, including bmp, jpeg format image display and storage, image processing, including KNN mean, KNN in value, Fourier transform, image segmentation. Platform: |
Size: 7801856 |
Author:fisher |
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Description: OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images.- OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images. Platform: |
Size: 2048 |
Author:ltrko9kd |
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Description: 数字图像处理电子书 by K.R.Castkeman 很好的参考价值-E-book digital image processing by KRCastkeman good reference value Platform: |
Size: 25607168 |
Author:tiger |
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Description: 一些常用的图像处理cpp和对应的matlab接口 是非常常用的一些代码-Quick list of the source included:
imhist_thresh.cpp: Generate histogram from data,# of bins based on unique values.
imsmarthist_thresh.cpp: equalize data based on histogram
imsmartstd_thresh.cpp: equalize data based on standard deviation
im_absdiff.cpp: Absolute difference of two images
im_add.cpp: Add two images
im_addelem.cpp: Add a variable to an image
im_complement.cpp: Inverse of an image
im_div.cpp: Divide one image by another (pixel wise, not linear algebra)
im_divelem.cpp: divide an image by an element
im_find.cpp: generate a new image based on conditions, will be booleanish
im_fliplr.cpp: Flip image left right
im_flipud.cpp: Flip image up down
im_hist.cpp: Histogram of image, notes will explain how to display results
im_log10.cpp: Take the log of the image
im_max.cpp: Max value in the image
im_mean.cpp: Mean value of the image
im_median.cpp: Median value of the image
im_min.cpp: Min value of the image
im_mult.cpp: Mult Platform: |
Size: 496640 |
Author:Ming |
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Description: 数字图像处理 中值处理 均值处理 直方图均衡化-Digital image processing deal with the mean value of histogram equalization deal Platform: |
Size: 3685376 |
Author:cfb |
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Description: 判断分析法从图象灰度直方图中把灰度值的集合用阀值 T分成两类，然后根据两个类的均值方差(类间方差)和各类的方差(类内方差)的比为最大来确定阀值。-Analysis to determine from the image histogram of the gray value threshold with the set T into two categories, and then based on two types of mean-variance (between-class variance) and various types of variance (intra-party worse) than to determine the threshold for the largest. Platform: |
Size: 88064 |
Author:qinyongming |
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Description: Source code of the MSSIM (Mean Structure Similitary Index). MSSIM is a measure of distortion static images. It s comparing distorted image with reference image and as the result return value between 0 and 1. The quality criteria is one of the most closer to MOS mean opinion score of image distortion. Platform: |
Size: 1024 |
Author:Alex |
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Description: 用Visual C++实现中值和均值滤波图像恢复处理程序实例-Using Visual C++ implementations of the value and the mean filter image restoration processing examples Platform: |
Size: 2048 |
Author:susan |
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Description: Normalises image values to 0-1, or to desired mean and variance
Usage:
n = normalise(im)
Offsets and rescales image so that the minimum value is 0
and the maximum value is 1. Result is returned in n. If the image is
colour the image is converted to HSV and the value/intensity component
is normalised to 0-1 before being converted back to RGB.
-Normalises image values to 0-1, or to desired mean and variance
Usage:
n = normalise(im)
Offsets and rescales image so that the minimum value is 0
and the maximum value is 1. Result is returned in n. If the image is
colour the image is converted to HSV and the value/intensity component
is normalised to 0-1 before being converted back to RGB.
Platform: |
Size: 1024 |
Author:mahmood |
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Description: 一种基于DWT的自适应数字水印算法。先将图像进行DWT分解，然后根据选定像素与其四邻域均值的关系，确定要嵌入的水印值。-DWT-based adaptive digital watermarking algorithm. DWT decomposition of the image first, then the selected pixel and its neighbors according to the relationship between the mean field, determine the value of the embedded watermark. Platform: |
Size: 169984 |
Author:wangran |
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Description: finding image value Mahalanobis Euclidean ,centroid and reshape the image-finding image value Mahalanobis Euclidean ,centroid and reshape the image.... Platform: |
Size: 1024 |
Author:dimpi |
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Description: 此文档中的代码可以计算5种图像的质量参数，分别是：图像灰度均值、图像方差、图像平均梯度、熵和峰值信噪比及均方误差。-The code in this document can be calculated five kinds of image quality parameters, namely: the image gray value, image variance, average gradient image, entropy and peak signal to noise ratio and mean square error. Platform: |
Size: 7168 |
Author:玄林江 |
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Description: ：采用双三次插值实现图像放大具有较高的图像质量，但运算量很大。在分析常用插值算法的基础上，提出一种基于区域的双三次 插值算法。该算法避免进行图像分割，通过被插值点四邻域像素的均值来划分图像的平坦区域和纹理细节复杂区域，采用不同的插值算法 进行计算。实验结果表明，与传统的双三次插值算法相比，该算法在保持放大后图像质量的同时，运算量降低 10 以上，具有一定的实用 价值。 -】Bicubic interpolation is an effective way to get well-qualified high-resolution image, but with high calculation load. The common used interpolation methods are discussed. A new region-based bicubic interpolation is proposed. Without segmenting the image, the mean value of the four neighboring points of the interpolated point is calculated which is used to divide the image into two regions: the flat region and the complex region with more details. Two different interpolating algorithms are chosen for each region. Experimental results show that the proposed algorithm can keep the image quality equal to the original algorithm while reducing the calculation load more than 10 percents. It is useful for applications. Platform: |
Size: 151552 |
Author:王国胜 |
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Search - mean value image