GeneticAlgorithm

利用维纳滤波实现噪声中的语音信号恢复，产生chirp信号，噪声为高斯白噪声，噪声叠加在chirp信号上，构成观测信号x(n),使用编程方法实现使用维纳滤波滤除高斯噪声。(Wiener filtering the voice signal recovery in the noise generated chirp signal, the noise is Gaussian white noise, noise superimposed on the chirp signal, constitute the observed signal x (n), using the programming method using the Wiener filter filter Gaussian noise.)

This program contains some basic image processing things, such as: 256 colors to grayscale, contrast stretching, anti-color, brightness change, etc.

图像处理课程设计——《人脸识别》，用matlab实现的，代码加实现，以及设计报告(Image processing designation of face recognize.)

Python+OpenCV实现的行人检测(Pedestrian Detection of Python + OpenCV Implementation)

实现人脸识别功能，GUI界面，其中有测试人脸集，识别率95以上(To achieve face recognition function, GUI interface)

一个颜色直方图的matlab源码，备注非常详细，可以实现(A color histogram matlab source code, notes are very detailed, can be achieved)

自然图像的梯度分布为重尾分布，超拉普拉斯分布，本代码通过概率统计画出梯度分布的曲线(The heavy-tailed distribution of gradients in natural scenes have proven effective priors for a range of problems such as denoising, deblurring and super-resolution.These distributions are well modeled by a hyper-Laplacian)

彩色图像融合 NSCT 实现红外与可见光图像融合(Color image fusion NSCT realize infrared and visible image fusion)

图像显著性，利用Itti视觉显著性分析算法，提取视觉对输入图像的感兴趣部分(Image salient regions)

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.)