SARBM3D_v10_win64

实现对一幅灰度和彩色图像作的离散余弦变换,选择适当的DCT系数阈值对其进行DCT反变换.(The realization of a piece of gray and color images for the discrete cosine transform, select the appropriate thresholds for DCT coefficients of its inverse transform DCT.)

主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)

用Matlab实现基于核函数的C均值聚类图像分割，实验好，好用(Using Matlab implementation of kernel-based C-means clustering image segmentation, experimental is good, easy to use)

一种基于小波的图像分块处理并且水印嵌入和提取，适合初学者学习使用(Based on wavelet image processing block and the watermark embedding and extraction, suitable for beginners learning to use)

三视图，用二维图像显示三位图像，分主视图，俯视图，侧视图(view)

该程序功能是实现对道路流动车辆统计。小模块功能有以下几个：1，对视频解帧并显示。2，对该视频训练背景图片。 3，利用背景图片用减背景法对测试视频进行前景提取，并进行阈值处理，图像分割，找出流动车的连通域。 4，对车辆进行统计。程序包内含有界面说明，以及程序使用的步骤和相关注意事项(The program function is to achieve movement of vehicles on the road statistics. A small module function has the following: 1 solution for video frames and displayed. 2, the video training background image. 3, using the background image used by the background method of testing the prospects for video extraction, and conduct threshold processing, image segmentation, to identify mobile car-connected domain. 4, vehicle statistics. Interface package contains instructions and procedures related to the use of the steps and considerations)

只能信息树立的相关课件和Matlab源代码，对于学习只能信息处理的学员很有帮助。(Information can only be set by the relevant courseware and Matlab source code, for students to study information processing can only be helpful.)

特征提取，主要是灰度共生矩阵和不变矩特征提取的程序，openCV下可直接运行(Feature extraction, mainly GLCM and invariant moments feature extraction procedures can be run directly under openCV)

说明：  多尺度多方向性的剪切波Shearlet变换优于小波变换，里面包含很多例子，可以直接运行，可以用于图像去噪，分割，增强等，是一个优于小波的图像稀疏表示工具(Shearlet transform of multi-scale and multi-directional shear wave is better than wavelet transform. It contains many examples and can run directly. It can be used for image denoising, segmentation and enhancement. It is an image sparse representation tool better than wavelet transform.)

针对目前工业制造领域面临的难题,提出利用非量测数字摄像机进行工业钣金件高精度三维重建与视觉检测.采用二维直接线性变换分解摄像机参数初值并结合光束法平差进行高精度标定 利用最小二乘模板匹配提取像面上的点、直线信息并进行混合光束法平差,从而进行钣金件的高精度三维重建及其尺寸制造误差的检测.所开发的视觉检测系统硬件成本低、自动化程度较高,实际数据的多次实验均取得了优于1/8 000的相对精度,说明所论述的方法为工业零件的自动化三维检测提供了一条可行途径.(View of the current challenges facing the field of industrial manufacturing, made use of non-metric digital camera precision sheet metal parts for industrial reconstruction and visual inspection. Using two-dimensional direct linear transformation and the decomposition of initial parameters of the camera bundle adjustment with high accuracy calibration extracted by the least square template matching, like the surface of point, line information and mixed bundle adjustment to the three-dimensional reconstruction of high-precision sheet metal parts and the size of the detection of manufacturing errors. visual inspection system developed by the hardware low cost, high degree of automation, the actual data, many experiments have achieved better than 1/8000 of the relative accuracy, that the methods discussed in the automation of industrial components to provide a feasible three-dimensional detection approach.)