搜索资源列表
face_detection
- 本文应用SMQT和 SPLIT UP SNOW 分类器来完成对人脸的检测。-The purpose of this paper is threefold: firstly, the local Successive Mean Quantization Transform features are proposed for illumination and sensor insensitive operation in object recognition. Secondly, a s
ezh
- 一种基于全局均值和局部方差的图像二值化方法-Based on the global mean and local variance image binarization
NLmeansfilter
- 进行对非局部均值算法的详细讨论包括权值的计算，均值的实现以及对于搜索窗口的讨论-Detailed discussion of the non-local means algorithm including the calculation of the weights, the realization of the mean and the discussion of the search window
BPpredictinof-flood
- 针对BP 算法易陷入局部极小、收敛速度慢等缺点，遗传算法是全局优化算法和具有很强的全局搜索能力，遗传算法优化BP 神经网络初始连接权值和阈值形成混合算法。以安徽宣城市为例,将汛期降水量作为预测对象，前期74 项大气环流特征量、500 hPa、100 hPa 月平均高度场、月平均海平面气压场和月平均海温场资料中选取预测因子，建立汛期降水短期气候预测模型。-BP algorithm is easy to fall into local minimum, slow convergence, genet
median-filter-alpha-trimmed-(
- 中值滤波，自适应alpha剪枝滤波器，均值滤波，可以有效减少噪声。-median filter alpha-trimmed (C++)mean filter adaptive,local noise reduction filter
COSFIRE
- COSFIRE是一个有效的滤波器，它可以自动的为图像画出轮廓，可以配置出gabor滤波器，配置一定的模糊参数和移位参数-A COSFIRE filter is automatically configured to be selective for a local contour pattern specified by a single example. The configuration comprises selecting given channels of a bank of Gabo
Matlab_learning_materials
- 主要包括图像的中值、均值去噪、非局部均值、分块局部去噪算法；还有均方误差和峰值信噪比评价、以及matlab基础学习资料如边缘检测、小波变化、灰度值转换等-Including image median, mean denoising, non-local means, block local denoising algorithm also mean square error and peak signal to noise ratio evaluation, and matlab based
EasyKrig_V3
- 克里金法广泛地应用于地下水模拟、土壤制图等领域，是一种很有用的地质统计格网化方法。它首先考虑的是空间属性在空间位置上的变异分布．确定对一个待插点值有影响的距离范围，然后用此范围内的采样点来估计待插点的属性值。该方法在数学上可对所研究的对象提供一种最佳线性无偏估计(某点处的确定值)的方法。它是考虑了信息样品的形状、大小及与待估计块段相互间的空间位置等几何特征以及品位的空间结构之后，为达到线性、无偏和最小估计方差的估计，而对每一个样品赋与一定的系数，最后 进行加权平均来估计块段品位的方法。-Krig
LeeFilt
- 噪声抑制的两个关键环节为建立真实后向散射系数的估计机制和制定同质区域像素样本的选择方案。Lee滤波是利用图像局部统计特性进行图像斑点滤波的典型方法之一，其是基于完全发育的斑点噪声模型，选择一定长度的窗口作为局部区域，假定先验均值和方差可以通过计算局域的均值和方差得到。-Two key aspects of the estimated noise suppression mechanisms for the establishment of the backscattering coefficie
ESNtools
- matlab下ESN的工具This software is intended for research use by experienced Matlab users and includes no warranties or services.-In alphabetical order here is what the routines are doing: analogToUnitCoded: - helper function for coding a 1-dim
ZaoShengXiaoChuDib
- 图像降噪处理：固定阈值法进行二值化、对二值图像的黑白点噪声消除、对二值图像进行消除孤立黑像素点、均值滤波处理、超限邻域平均法、n*n均值滤波处理、n*n中值滤波处理、十字型中值滤波、N*N最大值滤波、随机噪声处理、进行椒盐噪声处理、局部平均化处理。-Image noise reduction: fixed threshold binarization method for binary images in black and white spot noise elimination, the e
The_Magic_Of_Computer_Graphics
- 计算机图形学重要参考。对理解OpenGL和D3D的渲染过程有重要帮助。-Computer graphics is a vast field that is becoming larger every day. It is impossible to cover every topic of interest, even within a specialization such as CG rendering. For many years, Noriko Kurachi has reported
097-paste-with-non-function-macro
- expected-error {{no matching function foo found in local scope did you mean. -expected-error {{no matching function foo found in local scope did you mean.
as245
- Active Contour Models and Level Set algorithm, as well as several articles of the GVF, the list for the article: [1] Snakes Active Contour Models.pdf [2] Multiscale Active Contours.pdf [3] Snakes, shapes, and gradient vector flow.pdf [4] Motion of le
emd-method
- 经验模态分解(EMD Empirical Mode Decomposition )算法是Hilbert-Huang变换(HHT)的核心算法。经验模态分解(EMD)算法是通过算法过程定义的，而并非由确定的理论公式定义的，所以对其进行准确的理论分析非常困难，我们目前只能借助大量的数字仿真试验不断对其性能进行深入的研究。 EMD算法的目的在于将性能不好的信号分解为一组性能较好的本征模函数（IMFIntrinsic Mode Function ），且IMF须满足以下两个性质： (1)信号的极值点(极
WindsPhoto
- 支持本地上传和远程图片，自动盗链吝啬的国内门户提供的博客/空间/相册中的图片； 缩略图和列表两种方式显示，上传时自动生成缩略图，可以设置缩略图大小、文字水印和LOGO水印； 一键设置分类相册封面，自定义相册排序方式，正序或倒序； 相册集成HighSlide、LightBox、GreyBox、ThickBox特效，并可以使用外部的Z-Blog插件；-Supports local and remote upload images automatically mean Daolian do
bernsen
- The method uses a user-provided contrast threshold. If the local contrast (max-min) is above or equal to the contrast threshold, the threshold is set at the local midgrey value (the mean of the minimum and maximum grey values in the local window). If
imnoise_bi
- J = imnoise(I,'localvar',IMAGE_INTENSITY,VAR) adds zero-mean, Gaussian noise to an image, I, where the local variance of the noise is a function of the image intensity values in I. IMAGE_INTENSITY and VAR are vectors of the same size, and P
deimnoise2_bi
- adds zero-mean, Gaussian noise to an image, I, where the local variance of the noise is a function of the image intensity values in I. IMAGE_INTENSITY and VAR are vectors of the same size, and PLOT(IMAGE_INTENSITY,VAR) plots the functional
itoolbox
- 协同区间偏最小二乘 siPLS算法是 N rgaard等对其提出 的 iPLS方法的改进, 其基本算法步骤如下:(1)对原始谱图进行 预处理;(2)在全谱范围内建立全局偏最小二乘模型, 即上节的 模型;(3)在整个光谱区间采用 iPLS建立多个等窗口宽度的子 区间, 假设为 n个;(4)在每个子区间上建立偏最小二乘法模型, 即可得到 n个局部模型;(5)以交叉验证时的均方根误差 RMSE 值为各模型的精度衡量标准, 比较全光谱模型和各局部模型的 精度;(6)组合精度最高的局部子区间