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[Special Effects] ImageDIP2 DL : 0: “区域分割”是采用并行区域分割算法中的阈值化分割算法，阈值的选取方法是迭代阈值选取方法。 “边缘检测”是采用Prewitt边缘检测算子对图像进行边缘检测运算，Prewitt边缘算子的核心是两个3×3的卷积核（corrvolution kernel。- Segmentation is a parallel region segmentation algorithm thresholding segmentation algorithm, threshold selection method is iterative threshold selection method. Edge Detection is the edge detection using Prewitt operator image edge detection operator, Prewitt edge operator is the core of the two 3 × 3 convolution of the nuclear (corrvolution kernel.
Date : 2026-01-10 Size : 329kb User : 王文会
[Special Effects] FaceRecognitionUsingKernelDirectDiscriminantAnalys DL : 0: Face Recognition Using Kernel Direct Discriminant Analysis Algorithms and Matlab source codes for the kernel direct discriminant analysis (KDDA) -Face Recognition Using Kernel Direct Disc riminant Analysis Algorithms and Matlab sourc e codes for the kernel direct discriminant anal ysis (KDDA)
Date : 2026-01-10 Size : 727kb User : cy
[Special Effects] localnormalize DL : 0: LOCALNORMALIZE A local normalization algorithm that uniformizes the local mean and variance of an image. ln=localnormalize(IM,sigma1,sigma2) outputs local normalization effect of image IM using local mean and standard deviation estimated by Gaussian kernel with sigma1 and sigma2 respectively. Contributed by Guanglei Xiong (xgl99@mails.tsinghua.edu.cn) at Tsinghua University, Beijing, China. Inspired by the link: http://bigwww.epfl.ch/demo/jlocalnormalization/ -LOCALNORMALIZE A local normalization algorithm that uniformizes the local mean and variance of an image.ln = localnormalize (IM, sigma1, sigma2) outputs local normalization effect of image IM using local mean and standard deviation estimated by Gaussian kernel with sigma1 and sigma2 respectively.Contributed by Guanglei Xiong (xgl99@mails.tsinghua.edu.cn) at Tsinghua University, Beijing, China. Inspired by the link: http://bigwww.epfl.ch/demo/jlocalnormalization/
Date : 2026-01-10 Size : 1kb User : xj
[Special Effects] Gauss3D DL : 0: 3D的Gauss Kernel。可以应用于三维的数据处理-3D Gaussian Kernel. Can be applied to three-dimensional data processing
Date : 2026-01-10 Size : 14kb User : 安耀赫
[Special Effects] KernelIndependentComponentAnalysi DL : 0: Kernel Independent Component Analysis.这是核独立元分析的源程序-Kernel Independent Component Analysis. This is the nuclear element analysis of independent source
Date : 2026-01-10 Size : 98kb User : 何生
[Special Effects] gkde DL : 0: Gaussian Kernel Density Estimation with Bounded Support
Date : 2026-01-10 Size : 47kb User : baolij
[Special Effects] gaussian DL : 0: 高斯滤波核函数生成,可以根据K和要生成对应的高斯核-Gaussian filter kernel generation, according to K and to generate the corresponding Gaussian kernel
Date : 2026-01-10 Size : 1kb User : 刘靖
[Special Effects] KernelTracking DL : 0: A new approach toward target representation and localization, the central component in visual tracking of non-rigid objects, is proposed. The feature histogram based target representations are regularized by spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functions suitable for gradient-based optimization, hence, the target localization problem can be formulated using the basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyya coefficient as similarity measure, and use the mean shift procedure to perform the optimization. In the presented tracking examples the new method successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data association techniques is also discussed. We describe only few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking.-A new approach toward target representation and localization, the central component in visual trackingof non-rigid objects, is proposed. The feature histogram based target representations are regularizedby spatial masking with an isotropic kernel. The masking induces spatially-smooth similarity functionssuitable for gradient-based optimization, hence, the target localization problem can be formulated usingthe basin of attraction of the local maxima. We employ a metric derived from the Bhattacharyyacoefficient as similarity measure, and use the mean shift procedure to perform the optimization. In thepresented tracking examples the new method successfully coped with camera motion, partial occlusions, clutter, and target scale variations. Integration with motion filters and data association techniques is alsodiscussed. We describe only few of the potential applications: exploitation of background information, Kalman tracking using motion models, and face tracking .
Date : 2026-01-10 Size : 2.65mb User :
[Special Effects] KernelObjectTrack DL : 0: Kernel Object Tracking算法实现代码，自己本科毕设！-Kernel Object Tracking algorithm code, we completed the set up their own!
Date : 2026-01-10 Size : 107kb User :
[Special Effects] gaborfunction DL : 1: gabor_function1该程序对Gabor核函数某个尺度和方位的三维形状和二维平面图像进行显示 gabor_function2该程序对Gabor核函数五个尺度和八个方位的二维平面图像进行显示，共产生40个二维平面图像这两个程序对理解gabor小波很有帮助哦-gabor_function1 the program of Gabor kernel function of a scale and orientation of the three-dimensional shape and two-dimensional images show that the program gabor_function2 of Gabor kernel five scales and eight-directional two-dimensional images show that a total of 40 have a two-dimensional Planar images of these two procedures useful in understanding the gabor wavelet Oh
Date : 2026-01-10 Size : 1kb User : 吴海峰
[Special Effects] 1 DL : 0: 自适应核密度估计运动检测方法提出一种自适应的核密度(kernel density estimation, KDE)估计运动检测算法. 算法首先提出一种自适应前景、背景阈值的双阈值选择方法, 用于像素分类. 该方法用双阈值能克服用单阈值分类存在的不足, 阈值的选择能自适应进行, 且能适应不同的场景. 在此基础上, 本文提出了基于概率的背景更新模型, 按照像素的概率来更新背景, 并利用帧间差分背景模型和KDE分类结果, 来解决背景更新中的死锁问题, 同时检测背景的突然变化. 实验证明了所提出方法的适应性和可靠性.-Adaptive kernel density estimation method of motion detection of an adaptive kernel density (kernel density estimation, KDE) estimated motion detection algorithm. Algorithm first proposed an adaptive prospects, the background of the dual-threshold threshold selection method for pixel classification. The method used to overcome the dual-threshold single classification threshold shortcomings, the choice of threshold can be adaptive, and able to adapt to different scenes. On this basis, this paper, based on the probability of the background update model, in accordance with the probability of pixels to update the background, and take advantage of interframe differential background model and the classification results of KDE, to resolve the deadlock in the background update, while detection of abrupt changes in the background. Experiments show the proposed method of adaptability and reliability.
Date : 2026-01-10 Size : 1.41mb User : maolei
[Special Effects] drtoolbox.tar DL : 1: 这是一个MATLAB工具箱包括32个降维程序，主要包括 pca,lda,MDS等十几个程序包，对于图像处理非常具有参考价值- ，This Matlab toolbox implements 32 techniques for dimensionality reduction. These techniques are all available through the COMPUTE_MAPPING function or trhough the GUI. The following techniques are available: - Principal Component Analysis ( PCA ) - Linear Discriminant Analysis ( LDA ) - Multidimensional scaling ( MDS ) - Probabilistic PCA ( ProbPCA ) - Factor analysis ( FactorAnalysis ) - Sammon mapping ( Sammon ) - Isomap ( Isomap ) - Landmark Isomap ( LandmarkIsomap ) - Locally Linear Embedding ( LLE ) - Laplacian Eigenmaps ( Laplacian ) - Hessian LLE ( HessianLLE ) - Local Tangent Space Alignment ( LTSA ) - Diffusion maps ( DiffusionMaps ) - Kernel PCA ( KernelPCA ) - Generalized Discriminant Analysis ( KernelLDA )
Date : 2026-01-10 Size : 1.06mb User : yang
[Special Effects] KPCA DL : 1: 为解决PCA不适合多指标综合分析中非线性主成分分析的问题 ,采用核主成分分析 (kpca)方法 ,对我国不同地区 16种腐乳的品质进行了综合评价。 -PCA is not suitable to address the many indicators of a comprehensive analysis of non-linear principal component analysis of the problem, using Kernel Principal Component Analysis (kpca) method, 16 kinds of different regions of our country the quality of fermented bean curd had a comprehensive evaluation.
Date : 2026-01-10 Size : 1kb User : fengyu
[Special Effects] kde2d DL : 0: fast and accurate state-of-the-art bivariate kernel density estimator
Date : 2026-01-10 Size : 4kb User : yyz
[Special Effects] kernel DL : 0: Kernel-based 图像去噪和复原算法，是一种基于图像局部特征的复原方法。-Kernel-based algorithm for image denoising and restoration, is a local feature of image-based recovery methods.
Date : 2026-01-10 Size : 2.61mb User : feelfree
[Special Effects] androidkernelanalysis DL : 0: android的内核分析的文章，一个相当不错的文档！希望能对大家有所帮助！-android kernel analysis of articles, a pretty good document! Hope you can help!
Date : 2026-01-10 Size : 3kb User : 李春晖
[Special Effects] KernelBasedDeblurringToolBox_ver1 DL : 0: 运用核回归方法去模糊的经典程序，效果很好，有参考文献-using kernel regression for image deblurring,it s very effective
Date : 2026-01-10 Size : 10.17mb User : 向阳坡
[Special Effects] KLFDA DL : 0: 基于局部Fisher准则的非线性核Fisher辨别分析，应用于有监督的特征提取与高维数据的有效降维。-Kernel Local Fisher Discriminant Analysis for Supervised Dimensionality Reduction.
Date : 2026-01-10 Size : 2kb User : gameshadow
[Special Effects] kfcm DL : 0: 基于核函数的模糊C聚类均值（fcm）算法-FCM algorithm based on kernel function
Date : 2026-01-10 Size : 1kb User : 小飞
[Special Effects] Kernel-K_means DL : 0: 用IDL与ENVI二次开发进行非监督分类的Kernel K_means算法，强大实用-Use IDL and ENVI for the secondary development of Kernel K_means unsupervised classification algorithm, a powerful and practical
Date : 2026-01-10 Size : 4kb User : 李兴春

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