PF

PCA_进行indian_pines数据集合分类。((use PCA to classify the indian_pines data with train and test data in the rar))

对图像实现分块操作 很实用的程序(Realize the image sub-block operation is very useful procedure)

一种有效的匹配滤波估算地层品质因子的方法，精度较高，稳定性较好，值得借鉴(A kind of effective method of matched filtering to estimate formation quality factor, high precision, good stability, is worth using for reference)

说明：  几种常用的SAR图像滤波程序：初值滤波、中值滤波、维纳滤波、Lee滤波、kuan滤波等(some common filter program of SAR image,such as Lee filter,kuan filter.)

小波去噪,实现阈值小波去噪，并且含有frost去噪，并且输出信噪比(Wavelet denoising, to achieve the threshold wavelet denoising, denoising and contains frost, and the output signal to noise ratio)

说明：  基于MATLAB，对逐日的sst遥感数据做月平均并制作gif动图(Based on MATLAB, the daily SST remote sensing data are averaged monthly and the GIF map is made)

说明：  在稀疏域中，基于迭代阈值的线性反转问题，Daubechies 的经典外文文章，用于压缩感知(In the sparse domain, iterative threshold-based linear inversion problem, Daubechies classic foreign language articles for compressed sensing)

图象的直方图处理及全尺度变换和各种性能指标的计算，如psnr,mse等(image histogram processing and full scale transformation and various performance indicators, such as psnr, mse etc.)

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.)

针对分水岭算法存在的过分割问题以及VCH-F1切片图像的特点，提出一种能够有效消除局部极小值和噪声干扰的自动分割方法。首先比较彩色分量梯度图，选择分量图像的梯度信息，达到有效提取图像边缘信息的目的；然后提出基于多阈值分割的方法消除无效梯度信息；最后介绍了算法的步骤及结果。实验结果证明，通过该方法处理的梯度图像再进行分水岭算法处理，即使不进行区域合并也能达到很好的效果。(Watershed algorithm for over-segmentation problem of the existence of VCH-F1 as well as the characteristics of the image slice, a can effectively eliminate the local minimum value and noise automatic segmentation method. Comparing the first color component gradient map, select the quantity of image gradient information, achieve an effective extraction of image edge information purposes then made based on multi-threshold segmentation method to eliminate invalid gradient information Finally introduce the steps of the algorithm and results. Experimental results show that the adoption of the method of treatment of gradient watershed algorithm for image re-treatment, even if there is no regional merger will also achieve good results.)