wavelet_fusion

说明：  运用低通滤波器，中心削波和自相关技术估计一段男性和女性语音信号的基音周期，画出基音轨迹曲线，给出估计准确率。(The use of low-pass filter, the center clipping and related technologies is estimated from a male and female speech signal pitch period, pitch trajectory drawn curves of estimated accuracy.)

实现椭圆几何畸变矫正，将原始椭圆形变的图像，矫正为矩形正常图像(The correction of elliptical geometric distortion is achieved, and the original elliptical image is corrected to rectangle normal image.)

说明：  我是一个图象处理的初学者,用MATLAB语言编写了一些内部的函数,实现了图象处理的功能,比如entropy,laplician,otsu,top-hat等(image processing is a beginners MATLAB language some internal functions, achieving image processing functions, such as entropy, laplician, Otsu, top-hat, etc.)

图像处理,matlab文件，利用SURF进行图像拼接，完成图像配准(Image processing, matlab files, image stitching using SURF, image registration completed)

说明：  matlab 实现小波图像去噪，自编程序非调用库函数(matlab implementation of wavelet image denoising, non-self-compiled programs call library functions)

说明：  分布式合成孔径雷达成像仿真，包含像素级配准。(Distributed Simulation of synthetic aperture radar imaging, including pixel-level registration.)

isar成像处理，对测试数据进行处理的模板，可以显示二维像(ISAR imaging processing, the test data processing template, you can display the 2D image )

过特定人语音情感数据库的建立；语音情感特征提取；语音情感分类器的设计，完成了一个特定人语音情感识别的初步系统。对于单个特定人，可以识别平静、悲伤、愤怒、惊讶、高兴5种情感，除愤怒和高兴之间混淆程度相对较大之外，各类之间区分特性良好，平均分类正确率为93.7 。对于三个特定人组成的特定人群，可以识别平静、愤怒、悲伤3种情感，各类之间区分特性良好，平均分类正确率为94.4 。其中分类器采用混合高斯分布模型。(The system of speech emotion recognition)

一种二维EMD算法，作者是Anna Linderhed，该学者博士研究课题为二维EMD和小波变换，她的二维EMD算法与Nenus或其他学者的算法有较大的不同。(A two-dimensional EMD algorithm, the author is Anna Linderhed, her Ph.D. research topic is bidimensional EMD and wavelet transform. Her two-dimensional EMD algorithm is quite different from that of Nenus and other scholars.)

图像拼接！！此为本人的毕业设计源码，能完整远行，希望能对大家起到帮助。强烈鄙视那些为了骗取下载数而上载一些无关紧要代码甚至是编译错误一堆的卑鄙小人(Image mosaic! ! This is my graduation project source code can be a complete separation, I hope everyone can help. Strongly despise those who cheat in order to download and upload some irrelevant code compiler error or even a bunch of despicable villains)