matlab_register

说明：  灰度图像的边缘检测，包含多种算子：sobel,prewitt,gaosi算子等，包括原理和各算子的区别(Edge detection of gray image includes many operators: Sobel, Prewitt, Gaosi, etc)

矩形信号的frft（分数傅里叶变换wigner_ville_1.m 单分量信号去噪 wigner_ville_2.m 双分量平行信号去噪 wigner_ville_3.m 3分量信号频率检测）分数傅里叶变换是经典傅里叶变换的另一种改进方式。它的主要特点是提供研究对象从时间域到频率域全过程的综合描述，随着阶数从0连续增长到1，分数傅里叶变换展示出研究对象从纯时间域逐步变化到纯频率域的所有变化特征。因此，分数傅里叶变换提供了远比傅里叶变换多得多的可供选择的数据处理和分析方法。(The rectangular signal FRFT (Fractional Fourier Transform) Score Fourier transform is another modification of the classic Fourier transform. Its main feature is a comprehensive description of the study from the time domain to the frequency domain, with the order of continuous growth from 0 to 1, the fractional Fourier transform demonstrate the object of study from a purely time-domain gradually change to a pure frequency domain variation. Thus, the fractional Fourier transform provides data processing and analysis methods than Fourier transform much more to choose from.)

一种基于SIFT的图像配准方法，目前使用最广泛的一种配准方法。性能优。(One kind SIFT image registration method based on the most widely used kind of registration method. Excellent performance.)

亚像素边缘检测，基于zernike 灰度矩，实现精度可达0.05个pixel(sub-pixel edge detect)

说明：  对多帧图像进行超分辨率处理，得到一副高分辨率的单帧度图像。(Multi-frame image super-resolution processing, get a degree of high-resolution single-frame image.)

2014年西安电子科技大学数字图像处理上机实验，同时是研究生和本科生的代码及作业 (2014 Xi' an University of Electronic Science and Technology of digital image processing experiments on board, while the graduate and undergraduate students and job code)

说明：  SIFT特征提取演算法------可用于两张影像之特征点匹配(SIFT feature extraction algorithm-can be used for feature point matching of two images)

类似于photoshop软件处理，功能复杂简单耐用，适合于初学者学习参考(Similar to the photoshop software processing, functional complexity of simple and durable, suitable for beginners to learn information)

用matlab编写的区域生长法的程序，通过选择种子和阈值，可以进行图像分割和检查瑕疵(Written by matlab region growing process, by selecting the seeds and thresholds for image segmentation and inspection for defects)

YUV Quantization using VS2010