datamining

说明：  采用walsh进行处理，所得图片效果比较理想(Processed by walsh, results from the ideal image)

c# Ico图片文件转换成 bmp格式 实例源码

说明：  基于TensorFlow图像处理的小测试，里面的代码自己尝试过都可以运行。(Based on the TensorFlow image processing test, the code can run if it has tried.)

一个计算多边形面积和周长的程序, 同时可以把多边形显示出来, 直观展现多边形形状.(A polygon area and perimeter calculation procedures, the polygons can be displayed simultaneously, intuitive show polygonal shape.)

说明：  DIP关于各噪声和滤波概述，里面包含PDF和Latex(Dip overview of noise and filtering)

图像融合中的平均梯度、相关系数、信息熵、交叉熵、联合熵、均方误差、互信息、信噪比、峰值信噪比、均方根误差、空间频率、标准差、均值、扭曲程度、偏差指数等等(Average gradient, correlation coefficient, information entropy, cross-entropy, joint entropy, mean square error, mutual information, signal-to-noise ratio, peak signal-to-noise ratio, root mean square error, spatial frequency, standard deviation, mean, distortion degree, deviation index, etc. in image fusion)

此代码应用于图像分割，是基于类间方差的大津法求分割阈值(This code applies to image segmentation is based on the variance between two classes of Otsu threshold segmentation uated)

实现非负ICA的盲源分离，可用于对图像等非负混合信号的分离(Non-negative ICA blind source separation, can be used for the separation of mixed-signal images and other non-negative)

在本文中，我们提出了一个 所谓自适应模糊-K-均值聚类新方法 （AFKM）聚类的图像分割这可能是 适用于一般的图像和/或特定的图象（即 医疗和显微图像），采用不同的拍摄的 消费类电子产品，即，例如，在 普通数码相机和CCD相机(In this paper, we present a new clustering algorithm called Adaptive Fuzzy-K-means (AFKM) clustering for image segmentation which could be applied on general images and/or specific images (i.e., medical and microscopic images), captured using different consumer electronic products namely, for example, the common digital cameras and CCD cameras)

raw 数据转换成plant 的yuv 数据，已经测试通过。希望对raw数据进一步处理的同学有帮助。( Raw data is converted into YUV plant data, has been tested through. Hope that the raw data to further deal with the students to help. )