regiongrow2

网上下的CLAHE的matlab程序，原先运行有点问题，我修改了下，保证可以通畅运行了。(CLAHE algorithm for image enhancemnt)

内容为matlab的三维重建程序，达人可进来看，不适合初学者(Matlab says the three-dimensional reconstruction procedures, Tatsu can come watch, not suitable for beginners)

说明：  检测火灾，本课题为基于matlab的火灾检测识别，烟雾报警，火焰检测，通过几何参数判别，即面积增长率，角度等。完美运行。(Detection of fire, this topic is based on the MATLAB fire detection and recognition, smoke alarm, flame detection, through the geometric parameters, that is, area growth rate, angle and so on. Perfect operation.)

说明：  对二维图像进行分形维数的计算，采用差分盒维数进行计算，并且进行了拟合误差的计算(The fractal dimension of two-dimensional image is calculated by using the differential box dimension, and the fitting error is calculated)

这份代码是使用haar+adoboost做人脸检测用的，文件中还包括其他的特征选择，特征提取的算法，对于想做人脸检测这一块的朋友，可以下载来研究。(This code is used haar+adoboost human face detection, the document also includes other feature selection, feature extraction algorithm for face detection which one wants a friend, you can download to study.)

地震剖面代码,横坐标是时间，纵坐标是道数.(Seismic code, the abscissa is the time, the ordinate is the number.)

多边形填充 多边形裁剪 自定义多边形区域 自定义裁剪区域(Polygon fill polygon clipping custom polygon area custom crop area)

说明：  克里金插值（Kriging）在MATLAB中的实现（克里金工具箱）(Implementation of Kriging interpolation (Kriging) in MATLAB (Kriging toolbox))

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)

有详实的说明，基于C-V模型的图像分割，属于活动轮廓模型，有典型的图片例子，可以直接运行，适合研究生使用。(There are detailed instructions, CV model-based image segmentation, are active contour models, with typical picture examples can be run directly, for graduate students to use.)