real-pictures-imaging

演示了点阵字符的绘制方法，visual c++源码(Demonstrates a dot matrix characters drawing method, c++ source code)

针对CT 医学图像和MR I 医学图像成像特点, 提出了基于快速整数提升小波变换的融合方法。在CT 和 MR I 两幅医学图像配准的前提下, 利用提升小波变换把图像分解成低频和高频子图像, 对于小波变换后的高频 子图像, 选择区域标准差大的作为融合后的子图像 对于低频子图像, 采用加权融合, 最后进行小波逆变换, 得到 融合后的图像, 并对融合后图像用信息熵、平均梯度、相关系数的指标进行评价。实验结果表明, 基于快速整数提 升小波变换融合中, 小波高低频系数采用不同的规则能够取得更好的融合效果, 其轮廓清晰。该算法能够提升融 合后的医学图像信息量, 同时有效地保护图像的细节信息, 在执行时间和图像质量上均优于普通小波算法。(A imed at the characterist ics of CT andMR Imedical images, a new image fu sion al2 go rithm based on the fast in t lif t ing w avelet t ran sfo rm s is p ropo sed. Two o riginal images are decompo sed by the fast in t lif t ing w avelet t ran sfo rm s. The fu sion ru le based on the max imum standard deviat ion value variance is u sed to fu se the h igh f requency sub2image, w h ile a w eigh t2 ed average fu sed ru le is app lied by coeff icien t s of the low f requency. F inally, the fu sion image is recon st ructed fo r perfo rm ing inverse fast in t lif t ing w avelet t ran sfo rm s. The fu sion image is evaluated by en t ropy, average gradien t, and co rrelat ion coeff icien t s. Experimen tal resu lt show s that the fu sion image hasmo re info rmat ion than o riginal images and imp roves the quali2 ty of o riginal images. M eanw h ile, the fu sion image p ro tect s detail characterist ics of the image, thu s the real2t ime p rocess and image qualit ies are w ell than tha)

基于大津法和迭代法进行图像分割，分割结果较好(image segmentation based on otsu and interation)

说明：  K-均值聚类算法，对数据进行聚类分析，可用于提取关键帧等。用matlab实现(K-means clustering algorithm, cluster analysis of data that can be used, such as key frame extraction. Using matlab to achieve)

计算一个已归一化到单位区域的双峰值高斯函数(Calculation of a normalized unit area to the two-peak Gaussian function)

PWLS算法主要用于CT重建前的投影数据处理，能够很好的用于CT迭代算法中，对图像进行去噪(PWLS algorithm is mainly used for projection data processing before CT reconstruction. It can be well used in CT iterative algorithm to denoise images.)

指纹识别的MATLAB程序，包含了特征点抽取，特征点匹配，识别。(Fingerprint of the MATLAB program, including the feature point extraction, feature point matching, identification)

使用PCA和SVD进行数据去噪，利用数据主要的特征向量进行数据恢复和重建(Using PCA and SVD for data denoising)

基于基元共生矩阵的纹理特征提取。通过5个基本的方格来检测图像并生成图像的基元共生矩阵，并从矩阵中提取其纹理特征信息。(Texton occurrence matrix based texture feature extraction)

有关改良Canny算法的一些还算可以的文献(Improved Canny algorithm on some literature.)