matlab-TE-fault1

对输入视频进行处理，使用高斯背景建模的方法，得到视频前景，对于人群密度估计具有很大作用。(Processing of the input video, using a Gaussian background modeling method, to get videos prospects for population density estimation has a significant role.)

斐波那契数的实现算法及分析,标准化实验报告样本()

利用四元数对彩色图像进行各种图像处理的，如滤波、快速傅立叶变化、图像质量评价等。(Use quaternion various images for color image processing, such as filtering, fast Fourier transform, the image quality evaluation.)

说明：  基于遗传算法的图像融合，应用于求解图像融合的常用算法，matlab编写 ，很好的实现了，希望 对大家学习 有用(GA,Image Fusion Based on Genetic Algorithms)

数字图像处理中的滤波和傅里叶压缩，包括理想低通滤波器，巴特沃茨高通滤波器，高斯带通滤波器，高斯带阻滤波器，FFT图像压缩。附原图像和处理后的图像截图。(Digital image processing in filtering and Fourier compression, including the design of an ideal low-pass filter, design Batewoci high-pass filter, bandpass filter design Gaussian, Gaussian band stop filter, FFT image compression. Attached to the original image and processed image capture.)

说明：  基于harris角点特征的图像配准程序 matlab实现(Harris corner on the characteristics of matlab image registration process to achieve)

分别采用RGB模型和HIS模型对图像imageLane.bmp进行锐化，并比较锐化的效果是否相同（两锐化后的图像相减）。(RGB model and HIS respectively model imageLane.bmp sharpening the image and to compare the effect of sharpening is the same ( sharpen the image after the subtraction).)

matlab代码 用改进的八点算法求基础矩阵，进而求本质矩阵及相机外参。(improve eight)

说明：  ：基于主动轮廓识别和被动轮廓识别方法各自的优缺点，提出结合主动和被动的方法，先对图像进行被动轮廓的预处理，然 后再应用主动轮廓的方法，通过比较选出Canny算子进行预处理，再通过基于概率的方法分割图像，最后再应用Snake模型进行 轮廓提取。并取得较好的应用。(: Identification Based on Active Contour and passive contour recognition advantages and disadvantages of each method, proposed method of combining active and passive, passive first outline of the image pre-processing before applying the active contour method, by comparing the pre-selected Canny operator treatment, and then through the image segmentation method based on probability, and finally application of Snake model for contour extraction. And get better application.)

令x(n)=5exp(j*0.15*n*n)+6exp(j*300n-j*0.15*n*n) ，w(n)为高斯窗函数。试用matlab软件，取不同长度的窗函数，分别求x(n)离散短时傅里叶变换，并进行信号重构。(ORDER x (n) = 5exp (j* 0.15* n* n)+6exp (j* 300n-j* 0.15* n* n), w (n) for the Gaussian window function. Trial Matlab software, take different lengths of the window function x (n), respectively, seek to discrete short-time Fourier transform, and to reconstruct the signal.)