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AnimprovedBayesianfacerecognitionalgorithm
- 对人脸识别的贝叶斯方法ML中相似度计算公式进行了简化，对数据集的训练和人脸图像的预处理进 行了修改，提出了一种改进的贝叶斯人脸识另1】算法SML。在FERET人脸图像库的子集和南大人脸图像实验库上对 识别算法进行了测试和比较。实验表明，SML算法提高了ML算法的效率，克服了ML算法计算效率不高的缺陷，而 且SML的识别效率明显高于PCA方法。-Bayesian face recognition method on the ML in the similarity formula ha
matlab
- matlab 图像锐化 图像增强 高通滤波 巴特沃斯-image enhancement matlab image sharpening high-pass filter 波巴特沃斯
NBC
- 迁移朴素贝叶斯分类器算法实现，可用于高光谱遥感图像处理-Migration naive Bayes classifier algorithm can be used for hyperspectral remote sensing image processing
juinie
- 基于混沌的模拟退火算法，毕设内容，高光谱图像基本处理，利用贝叶斯原理估计混合logit模型的参数。- Chaos-based simulated annealing algorithm, Complete set content, basic hyperspectral image processing, Bayesian parameter estimation principle mixed logit model.
hing_v32
- 毕设内容，高光谱图像基本处理，模拟数据分析处理的过程，包括主成分分析、因子分析、贝叶斯分析。- Complete set content, basic hyperspectral image processing, Analog data analysis processing, Including principal component analysis, factor analysis, Bayesian analysis.
qei
- 高斯白噪声的生成程序，相参脉冲串复调制信号，用于图像处理的独立分量分析。- Gaussian white noise generator, Complex modulation coherent pulse train signal, Independent component analysis for image processing.
fai_jt36
- 有借鉴意义哦，图像的光流法计算的matlab程序,高斯白噪声的生成程序。- There are reference Oh, Image optical flow calculation matlab program, Gaussian white noise generator.
61549815ppb
- ppb一种ppb滤波算法来去除图像中的加性高斯噪声，09年才提出来的新算法非常的高效，去噪效果相当好(This MATLAB software implements the denoising algorithm (the Probabilistic Patch-Based filter) for images damaged by multiplicative Nakagami-Rayleigh noise as presented in: Iterative Weighted Maximum
ML
- GMM高斯混合模型EM算法聚类，PCA主成分分析，以及从人脸图像中提取主成分(GMM Gauss hybrid model EM algorithm clustering, PCA principal component analysis, and extraction of principal components from face images)
lizhengxiugai4
- 这是关于图像去噪的一种高斯牛顿方法，本代码有一个缺点就是:去噪效果不怎么好(this is a proceture about image denoising;it is based on TOF model)
threefilterCompare
- 将图像傅里叶变换，然后利用高斯、巴特沃斯、理想滤波器实现图像高频成份和低频成份的分离。(The image Fu Liye transform is applied, then the Gauss high pass lowpass filter is used to achieve the separation of high-frequency components and low frequency components.)
CFAR
- 基于高斯分布的CFAR检测算法(双参数CFAR检测)，输入一个确定的虚警概率，在满足一定虚警率的情况下对图像进行分割，实现目标与背景的分离。(The CFAR detection algorithm based on Gauss distribution (two-parameter CFAR detection) inputs a certain false alarm probability, and segmentes the image to achieve the separation