FBP_recn

SVM算法的线性分类，图像分类单幅遥感图像特征提取分类(Linear classification of SVM algorithm, image classification, feature extraction and classification of single remote sensing image)

提出一种基于非采样contourlet变换的红外与可见光图像融合方法。高频系数结合活性度量和多分辨率系数间相关性来实现加权融合；低频系数通过局部梯度进行活性度量，再采用加权与选择相结合的规则。(Proposed a contourlet transform infrared and visible image fusion method based on non-sampling. The high-frequency coefficient binding activity to measure the correlation between multi-resolution coefficient weighted fusion activity measure low frequency coefficients of the local gradient, and then weighted and selection combining rules.)

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.)

比较新的图像处理类，2010版，并且有DEMO,方便应该(Relatively new class of image processing, 2010 Edition, and has DEMO, should facilitate)

用于植物叶片分类的图形界面,是Matlab源码，用BP神经网络实现(For plant leaf classification graphical interface, the Matlab source code, using BP neural network)

新发表论文Graph cuts based active contour model with selective local or global segmentation 附源码，基于图割的主动轮廓模型，用于有选择的局部分割或全局分割，欢迎下载！(Published Graph cuts based active the contour the model with selective local or global a segmentation attached source, the active contour model based on graph cuts for selected local partition or global segmentation are welcome to download!)

基于小波变换的人脸识别代码本代码对图像进行小波分解，然后又用最近邻方法实现了图像的识别。(Face Recognition Based on Wavelet Transform code-wavelet based face recognition, the code of the image wavelet decomposition, and then with the nearest neighbor method to achieve the image recognition!)

包含滤波模板，形态学运算，边缘检测结合经自己修改过的hough变换编写的vc程序，成功检测机场跑道和任何图像中最明显的现状特征，经测试，检测精度高。对学习vc编程用于图像处理有帮助。(hough transform based image processing package which is useful for detecting airfield like straight line features.)

基于图像对比度和波段相关性的波段选择算法，适用于高光谱图像的特征选择(Bands selection algorithm based on image contrast and correlation of bands for hyperspectral image feature selection)

本方法的种子点选取采用Harris角点法，阈值则通过云模型获得，对lena图像进行了较好的分割(The method selected seed points using Harris corner point method, the threshold is obtained through the cloud model, for better lena image segmentation)