matlab

在Matlab中建了图形用户界面，采用不同特征提取方式，如gray，color，lbp，灰度共生矩阵GLCM等，对数据集中的影像进行场景检索。(Graphic user interface is built in Matlab. Scene retrieval of images in dataset is carried out by using different feature extraction methods, such as gray, color, lbp, gray level co-occurrence matrix (GLCM).)

Computing regularization paths for learning multiple kernels另一个多核学习算法 可用于多类分类 目标检测(Computing regularization paths for learning multiple kernels The other multicore learning algorithm for multi-class classification target detection)

Image processing functions: Gamma correction Contrast stretching histogram equalization

彩色图像的威纳滤波去噪算法，很简单的，很全，自己毕业论文的程序(Color image of the Wiener filter denoising algorithm, very simple, very full, their thesis program)

marburg.c 用Burg算法求AR模型的参数。 mar1psd.c 由AR模型参数得到功率谱。 maryuwa.c 用Levinson算法求解Yule-Walker方程以得到 阶AR模型的参数 。 (marburg.c using Burg algorithm for AR model parameters. mar1psd.c by the AR model parameters obtained power spectrum. Levinson algorithm maryuwa.c with Yule-Walker equation in order to get rank AR model parameters.)

说明：  快速图像修复的各种算法 各种算法详尽的表述及其相互比较(Fast image restoration algorithms detailed presentation of the various algorithms are compared)

文简要介绍了指纹识别的基本步骤，分别是指纹图像预处理、指纹特征提取、指纹匹配(This paper briefly introduces the basic steps of fingerprint recognition, which are fingerprint image preprocessing, fingerprint feature extraction and fingerprint matching)

db4小波的提升小波分解，从已发表的论文中得来，可放心使用(db4 wavelet lifting wavelet decomposition, the published papers come, you can be assured)

说明：  Latent SVM算法实现行人检测opencv(Latent SVM Pedestrian Detection Based on Algorithms opencv)

孔径雷达图像固有的相干斑噪声严重降低了图像的可解译程度，影响了后续目标检测、分类和识别 等应用。因此，SAR图像的相干斑抑制问题一直是SAR图像应用的重要课题之一。一个理想的去斑算法应该在平 滑的同时保持图像的边缘等细节不受损失，目前存在各种各样的算法，但没有一种方法能够完美的满足这一要求。 本文对SAR图像的相干斑抑制问题进行了全面系统的研究，分析了相干斑的形成原因，总结了目前存在的相干斑 抑制算法的主要思路，介绍了具有代表性的算法，并对各种算法的性能进行了定性分析和比较，给出了去斑算法定 量评估方法(The inherent speckle noise of the aperture radar image seriously reduces the degree of interpretation of the image, and affects the detection, classification and recognition of the subsequent targets. And other applications. Therefore, the problem of speckle suppression in SAR images has been one of the most important topics in the application of SAR images. An ideal speckle algorithm should be flat At the same time, the details such as edges of images are not lost. There are various algorithms at present, but none of them can satisfy this requirement perfectly.)