corner-detection

水平集边缘检测代码，利用了变分法进行优化和处理，实现了图像的快速边缘检测(Level set edge detection code is optimized and processed by using variational method, and fast edge detection of image is realized.)

本实验要求编写一个计算压缩-解压缩图像的均方根误差、均方信噪比的程序。该程序是一个通用程序。编写程序产生图示的结果。使用上面的保真度准则程序计算可视信息的损失特性。(Prepared in this experiment, a calculation of compression- decompression of the root-mean-square error of image, mean square signal to noise ratio of the procedure. The procedure is a common procedure. Picture shows the preparation of the results of procedures. The use of the above criteria for the fidelity of calculated loss characteristics of visual information.)

利用C++实现了BMP图像的读入和显示利用C++实现了BMP图像的读入和显示利用C++实现了BMP图像的读入和显示(Use C++ achieve the BMP image to read and display BMP images using the C++ achieve to read and display BMP images using the C++ achieve to read and display)

自己写的一种查找图像边缘的方法，效果还不错(a way to find the edge of a picture by myself, and it can reach good result)

可以打开各种图像格式，并显示，很好很强大(Can open a variety of image formats)

这是图像恢复中的盲反卷积迭代算法的matlab的源程序，对于学习数字图像有很大的好处！(This is image restoration in the Iterative Blind Deconvolution algorithm matlab source for the study of digital image has a lot of benefits!)

颜色、形状、纹理特征提取算法及应用,各种方法都有，很有用。(Color, shape, texture feature extraction algorithms and applications, various methods are very useful.)

视觉引导车路识别：灰度AGV路径识别；彩色AGV路径识别；HSI彩色空间的AGV路径识别；路径中心线的定位；Radon变换的AGV路径偏差检测(Vision Guided Vehicle Road Identification: gray AGV path identification color AGV path identification HSI color space of the AGV path identification path centerline positioning Radon transform of the AGV path deviation Detected)

LMMSE图像超分辨率重建，基于先验知识的图像超分辨率重建(LMMSE image super-resolution reconstruction, image super-resolution reconstruction based on prior knowledge)

说明：  卷积神经网络（Convolutional Neural Network）是一个专门针对图像识别问题设计的神经网络。它模仿人类识别图像的多层过程：瞳孔摄入像素；大脑皮层某些细胞初步处理，发现形状边缘、方向；抽象判定形状（如圆形、方形）；进一步抽象判定（如判断物体是气球）。(Convolutional neural network is a neural network specially designed for image recognition. It imitates the multi-layer process of human recognition image: pupil ingestion of pixels; some cells in the cerebral cortex preliminary processing to find shape edges and directions; Abstract judgment of shape (such as circles and squares); and further Abstract judgment (such as judging objects are balloons).)