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本书是计算机视觉编程的权威实践指南,依赖 Python 语言讲解了基础理论与算法,并通过 大量示例细致分析了对象识别、基于内容的图像搜索、光学字符识别、光流法、跟踪、三维重建、 立体成像、增强现实、姿态估计、全景创建、图像分割、降噪、图像分组等技术。(This book is an authoritative guide to computer vision programming, which explains basic theories and algorithms based on the Python language.A large number of examples carefully analyze object recognition, content based image search, optical character recognition, optical flow, tracking, 3D reconstruction,Stereoscopic imaging, augmented reality, attitude estimation, panoramic creation, image segmentation, noise reduction, image grouping and other techniques.)

利用数学形态学构成形态学滤波器对图象进行滤波,处理效果较满意.(using mathematical morphology constitute morphological filter image filtering, processing more satisfied with the results.)

说明：  这个压缩包里只要给出了边缘保持系数和等效视数的计算方法(This compression is given as long as the edge of the bag to maintain the equivalent depending on the number of coefficients and the calculation of)

WAVEPASTE将系数放在小波分解结构中。(WAVEPASTE Puts coefficients in a wavelet decomposition structure.)

说明：  利用matlab实现基于帧间差分的运动目标检测(Moving target detection based on inter frame difference using MATLAB)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

图像处理的IPP库使用手册，包括每个函数的使用说明，以及参数的意义。(IPP library of image processing using the manual, including instructions for each function, as well as the significance of the parameters.)

说明：  同态滤波利用去除乘性噪声(multiplicative noise)，可以同时增加对比度以及标准化亮度，借此达到图像增强的目的。(Homomorphic filtering can increase contrast and standardize brightness simultaneously by removing multiplicative noise, so as to achieve the purpose of image enhancement.)

关于计算机视觉和图像的matlab工具箱。包括相位一致性特征，空间特征检测，积分图像，非极大值抑制和滞后阈值，边链接和线段拟合，去噪，等(MATLAB and Octave Functions for Computer Vision and Image Processing。such as • Feature Detection via Phase Congruency • Spatial Feature Detection • Integral Images • Non-Maxima Suppression and Hysteresis Thresholding • Edge Linking and Line Segment Fitting • Test Grating for Edge Detection • Image Denoising • Surface Normals to Surfaces • Scalogram Calculation • Anisotropic diffusion • Grey Scale Transformation and Enhancement • Frequency Domain Transformations • Functions Supporting Projective Geometry • Feature Matching • Model Fitting and Robust Estimation • Fingerprint Enhancement • Interesting Synthetic Images • ASCII Image Generation • Rotation Transforms • Image Blending • Colourmaps and colour conversions • Image Display, Image Writing and Miscellaneous )

压缩传感，MATLAB，信号重建，正交匹配追踪，打破乃奎斯特定理(Compressed sensing, MATLAB, signal reconstruction, orthogonal matching pursuit, breaking the Nyquist Theorem)