MCA

该数字图像处理文件有很强的修改能力，可以仔细的分析每一个频域不同条件下的实验结果分析。有很强的处理图像能力(The digital image processing of documents has a strong ability to change and be more careful analysis of each under different conditions, a frequency-domain analysis of the experimental results. Has a strong ability to deal with images)

混合高斯模型使用K（基本为3到5个） 个高斯模型来表征图像中各个像素点的特征,在新一帧图像获得后更新混合高斯模型,用当前图像中的每个像素点与混合高斯模型匹配,如果成功则判定该点为背景点, 否则为前景点。通观整个高斯模型，他主要是有方差和均值两个参数决定，,对均值和方差的学习,采取不同的学习机制,将直接影响到模型的稳定性、精确性和收敛性。由于我们是对运动目标的背景提取建模，因此需要对高斯模型中方差和均值两个参数实时更新。为提高模型的学习能力,改进方法对均值和方差的更新采用不同的学习率 为提高在繁忙的场景下,大而慢的运动目标的检测效果,引入权值均值的概念,建立背景图像并实时更新,然后结合权值、权值均值和背景图像对像素点进行前景和背景的分类。(Gaussian mixture model using K (essentially 3-5) Gaussian model to characterize the features of each pixel in the image, in the image of the new frame for updated Gaussian mixture model, with each pixel in the image with a Gaussian mixture current model matching, if successful, determined that the point of the background points, otherwise the former attraction. Throughout the entire Gaussian model, he mainly has two parameters determine the variance and the mean, the mean and variance of the study, to take a different learning mechanism, will directly affect the stability, accuracy and convergence model. Since we are moving object extraction of the background modeling, so the need for the Gaussian model variance and mean two parameters real-time updates. In order to improve the learning ability of the model, an improved method for updating the mean and variance of different learning rates to improve in the busy scene, large and slow moving object detection results, the introduction of)

三自由度并联机器人工作空间求解matlab程序，用球坐标分割的空间(workspace for solution)

说明：  通过多尺度分解，实现医学图像的图像融合，达到更好的效果(Through multi-scale decomposition, medical image fusion can be achieved to achieve better results.)

使用sift+RANSAC完成两幅图像的特征提取和匹配，并将较小图像区域在另一幅中用方框圈出来。运行plot.m。(This code uses sift and RANSAC to extract features of two images and then finds and marks the smaller image in the other image.run plot.m)

将RGB格式的图片进行mosaic处理得到RawData格式的图片，然后再恢复成RGB格式彩色图片,laroche-CFA插值算法(turn an RGB picture to RawData picture，then recover the RawData picture to an RGB picture.it is called laroche-CFA.)

说明：  基于双边滤波的retinex算法，暗光图像增强，有效去噪、提高对比度、去光晕；含论文和讲解PPT、实例代码(Retinex algorithm based on bilateral filtering can enhance dark image, effectively denoise, improve contrast and eliminate halo)

2016华为软件精英挑战赛，采用迪杰斯特拉算法，效率高，但需要自行修改(HUAWEI software challenge 2016)

有关图像的目标识别："给出一种基于特征分类辨识的合成孔径雷达图像目标检测方法#用恒虚警和扩展分形方法对3&E图像进行目 标检测后用面积和峰值能量比算子辨识目标和背景杂波!去除一部分虚警!用小波域主成分分析对每个检测窗口内的图 像提取特征向量!用支持向量机对提取得到的特征向量进行分类!辨识目标和背景杂波!完成目标检测#使用&K?3数 据对该方法进行验证和分析!实验结果表明!经过特征分类辨识后!在检测率不变的情况下!虚警数目显著降低# (Related to the image target recognition)

一种基于背景减法和帧差的运动目标检测算法(Based on background subtraction and frame difference moving target detection algorithm)