2-Matlab-SIFT

说明：  使用pca方法对图像进行特征提取，对训练集的20个人的共一百张人脸进行训练，使用adaboost算法生成强分类器，可以对测试集的人脸图片进行识别，且识别率较高(The PCA method is used to extract the features of the image, and the training is carried out for a total of 100 faces of 20 people in the training set. The AdaBoost algorithm is used to generate a strong classifier, which can recognize the face images in the test set with a high recognition rate)

说明：  分子图像处理的软件，但没有数据库，具体操作看操作说明(Molecular image processing software, but there is no database, see the specific operation instructions)

robustly fits a homography to a set of putatively matched image points(robustly fits a homography to a set of putat ively matched image points)

将原图像进行退化处理（选择大气湍流导致图像模糊时相应的PSF），然后将退化后的图像进行复原（使用维纳滤波、直接逆滤波）.(The original image degradation process,and then restore the degraded image with Wiener filtering and inverse filtering.)

自己编写的单应性矩阵的求法，按照张正友的论文进行编写的。希望有用。(I have written the homography method, according to Zhang Zhengyou papers prepared for. I hope useful.)

Image Fusion With Guided Filtering基于向导滤波的图像融合。将图像分解成基础层和细节层，用一种新型的滤波融合图像，使融合效果更显著更高效。(The image is decomposed into a base layer and layer of detail, the fused image with a new filter, the fusion effect is more pronounced and more efficient.)

实现图像的分块压缩感知重建，DCT变换，OMP重构算法(Image block compressed sensing reconstruction, DCT transform OMP reconstruction algorithm)

canny边缘检测的步骤： 1，生成高斯核，与图像做卷积 2，计算梯度图像 3，非极大值抑制 4，双阈值法和连接边缘(Canny edge detection steps: 1, Generate Gaussian kernel, convolution with the image 2, calculate the gradient image 3, non-maximal inhibition 4, double threshold method and connect the edge)

题目： 八宝粥的生产过程中需要用到大量的红豆（红蚕豆），而实际上从红豆产地购买得到的红豆中会参杂一些杂物和不合格红豆。为了保证八宝粥的质量，需要对红豆进行筛选，去除不合格红豆和其它杂物。目前国内在红豆筛选工序上仍然使用人工筛选的方式，存在人工成本高、精确度差、劳动强度大等缺点。因此八宝粥生产厂商迫切需求开发一款能够自动实现红豆筛选的自动化筛选机。针对上述需求，请设计筛选机中的基于可见光图像的红豆筛选算法，该算法应尽可能的准确的找到参杂在红豆原料中的不合格红豆和杂物。 附件包括两个不同实验环境下拍摄得到的红豆相关图片样本库，实验环境分别为自然光照条件和灯光条件。每个条件下的样本库包括合格、不合格、杂物和混合四类样本的图像，其中合格、不合格以及杂物的图像可用来训练或建模，混合类图像用来测试算法的准确性和实时性。同学可在自然光照环境下的样本库或者灯光条件下的样本库中任选其一，用于解决上述问题。 作业提交格式包括以下四个内容： 一、 问题分析 二、 算法设计 三、 实验结果(将自己选择的样本库中的混合样本图片中的样本个体进行分类，并给出可视化的分类结果。) (Title:Use a lot of red bean production process of eight-treasure porridge ( red bean ), but in fact from the Red areas available in red bean can blend some sundries and unqualified red bean. In order to ensure the quality of eight-treasure porridge, the need for screening of red bean, red bean and other debris removal is not qualified. At present in the domestic bean screening process still use manual screening method, has the disadvantages of high labor costs, poor accuracy, high labor intensity. Therefore, eight-treasure porridge manufacturers need to develop a can achieve automatic bean screening automatic screening machine. According to the above requirements, please design screening machine selection algorithm based on visible light image of the red, the algorithm should be as accurate as possible to find the mixed in the bean raw materials in the unqualified red bean and debris.Accessories include captured in two different experimental environment of the red bean image sample dat)

双数复小波变换及其图像去噪算法。。。。。(Double the number of complex wavelet transform and image denoising algorithm. . . .)