Compressive-Classifier

选择一副灰度图像，用区域分裂合并法对其进行分割(Choose a grayscale image, with its regional divisions split merge method)

说明：  按照最邻近原则把待分类样本点分到各个簇。然后按平均法重新计算各个簇的质心，从而确定新的簇心。一直迭代，直到簇心的移动距离小于某个给定的值。(According to the nearest neighbor principle, the sample points to be classified are divided into clusters. Then the centroid of each cluster is recalculated according to the average method to determine the new cluster center. Iterate until the moving distance of the cluster center is less than a given value)

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

discrete hartley trnasform paper

说明：  本程序为傅里叶变换，给定初始时域波形，可得到对应频域波形。可出图(The program is Fourier transform. Given the initial time-domain waveform, the corresponding frequency-domain waveform can be obtained. Drawing out)

一个很不错的指纹分析算法源代码，可以从采集的指纹图片中进行二次黑白化，平滑图像处理。可以对指纹图像特征信息提取，比对，以轮廓显示以及色彩覆膜特显等技术算法。主要的分析速度很快，值得学习的算法。要在指纹信息处理中比较不错，本站隆重推荐。(A very good fingerprint analysis algorithm source code, from the collection of fingerprint images, the second black and white, smooth image processing. Fingerprint image feature information extraction, compared to the contour display and color coated special significant technical algorithm. Analysis fast, it is worth learning algorithm. Fingerprint information processing site is highly recommended.)

混合高斯(Mixture of Gaussian, MOG) 背景建模算法和Codebook 背景建模算法被广泛应用于监控视频的运动目标检测问题, 但混合高斯的球体模型通常假设RGB 三个分量是独立的, Codebook 的圆柱体模型假设背景像素值在圆柱体内均匀分布且背景亮度值变化方向指向坐标原点, 这些假设使得模型对背景的描述能力下降. 本文提出了一种椭球体背景模型, 该模型克服了混合高斯球体模型和Codebook 圆柱体模型假设的局限性, 同时利用主成分分析(Principal components analysis, PCA) 方法来刻画椭球体背景模型, 提出了一种基于主成分分析的Codebook 背景建模算法. 实验表明, 本文算法不仅能够更准确地描述背景像素值在RGB 空间中的分布特征, 而且具有良好的鲁棒性.(The background modeling algorithm of mixture of Gaussian (MOG) and codebook is widely used in moving object detection of surveillance video. However, the ball model of MOG usually assumes that the three components of RGB are independent, while the cylinder model of codebook assumes that the value of background pixel is distributed uniformly within the cylinder and the changing direction of brightness points to the origin of the coordinate system. These assumptions reduce the descriptive capability for background modeling. Therefore, the paper proposes an ellipsoid- based background model, which overcomes the MOG and codebook0s limitations. By using principal component analysis to depict the ellipsoid background model, a novel PCA-based codebook background modeling algorithm is proposed. Experiments show that this algorithm can not only give more accurate description of the distribution of background pixels but also have a better robustness.)

本代码是基于数学形态学的多尺度多结构算子的腐蚀与膨胀算法(This code is corrosion and expansion algorithm based on mathematical morphology of multi-scale multi-structure operator)

选择合适的样本特征点，然后可以将特征导入svm进行分类(After the image processing, the main information is obtained by PCA transform, and then the feature of texture information selection is put forward)

winform 仿QQ截图，可将截图直接保存到内存中 附完整源码下载