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redeye
说明： matlab去除红眼，用户手动绘制需要去红眼的区域，并选择参数，进行操作。(matlab remove red eye, the user need to manually draw the red-eye area, and select the parameters to operate.)
- 2010-03-20 15:39:06下载
- 积分：1
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BDFTT4_doublea
一种基于DFT的瞬时测频算法，及及插值算法，最后由图形表示测频结果。
(Instantaneous frequency of the DFT-based algorithm, and the interpolation algorithm, by the graphical representation of the frequency measurement results.)
- 2012-08-13 08:59:59下载
- 积分：1
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OPTA
传统图形细化算法，每条代码有详细注解，适合新手。(Traditional graphics thinning algorithm, each code have detailed notes.
)
- 2012-03-29 19:21:31下载
- 积分：1
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基于多尺度形态学提取眼前节组织
基于多尺度形态学提取眼前节组织，已经调试成功，效果明显，可直接使用(Extraction of anterior segment tissue based on multi-scale morphology has been successfully debugged, and can be used directly.)
- 2018-04-19 16:45:17下载
- 积分：1
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processing5
图像基础处理——透视矫正的程序代码，把图像还原(Image basic processing- perspective correction code to restore image)
- 2013-04-10 11:29:49下载
- 积分：1
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MATLABon-wavepack
应用MATLAB小波工具箱中的一维小波包分析函数,采用默认阈值、调节后的阈值两种方法对含噪声的信号进行处理,并以一可见吸收光谱降噪为例,说明该方法在信号降噪中有效可行.
(Application of MATLAB wavelet toolbox one dimensional wavelet packet analysis function, using the default threshold value, the adjusted threshold value of two kinds of methods including noise signal processing, and with a visible absorption spectrum noise reduction as an example to show the method is effective in signal noise reduction is feasible.
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- 2021-01-13 15:48:49下载
- 积分：1
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tuxiang
利用支持向量机对图像进行分割。特征属性为RGB图像3个通道的亮度。(Using support vector machines for image segmentation. Characteristic properties of three channels of RGB image brightness.)
- 2011-08-05 19:13:22下载
- 积分：1
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Image-conversion
此算法是图像之间的转换，二值图，RGB等的相互转换源代码(This algorithm is the conversion between the images, the two value of the map, RGB, and so on the conversion of the source code)
- 2015-09-18 20:17:30下载
- 积分：1
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quantum
量子图像加密 模拟BB84规则 对图像进行加密(quantum signal processing)
- 2020-11-04 10:09:51下载
- 积分：1
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FAST-ICA
1、对观测数据进行中心化，；
2、使它的均值为0，对数据进行白化—>Z；
3、选择需要估计的分量的个数m，设置迭代次数p<-1
4、选择一个初始权矢量（随机的W，使其维数为Z的行向量个数）；
5、利用迭代W(i,p)=mean(z(i,:).*(tanh((temp) *z)))-(mean(1-(tanh((temp)) *z).^2)).*temp(i,1)来学习W （这个公式是用来逼近负熵的）
6、用对称正交法处理下W
7、归一化W(:,p)=W(:,p)/norm(W(:,p))
8、若W不收敛，返回第5步
9、令p=p+1，若p小于等于m,返回第4步
剩下的应该都能看懂了
基本就是基于负熵最大的快速独立分量分析算法(1, on the center of the observation data, 2, making a mean of 0, the data to whitening-> Z 3, select the number of components to be estimated m, setting the number of iterations p < -1 4, select an initial weight vector (random W, so that the Z dimension of the row vectors of numbers) 5, the use of iteration W (i, p) = mean (z (i, :).* (tanh ((temp) ' * z)))- (mean (1- (tanh ((temp)) ' * z). ^ 2)).* temp (i, 1) to learn W (This formula is used to approximate the negative entropy) 6 with symmetric orthogonal treatments W 7, normalized W (:, p) = W (:, p)/norm (W (:, p)) 8, if W does not converge, return to step 5 9 , so that p = p+1, if p less than or equal m, return to step 4 should be able to read the rest of the basic is based on negative entropy of the largest fast independent component analysis algorithm)
- 2013-06-27 15:39:00下载
- 积分：1
