matlab

基于Hog特征 SVM分类器，利用Opencv3.0进行手写数字识别的源代码及所需资源文件（训练图片、测试图片）

说明：  图像处理，通过matlab程序实现视频插帧的功能(Image processing and video frame insertion through MATLAB program)

图像校正的Matlab代码，非常不错，可以实现很好的校正结果，速度也很快(Image correction of Matlab code, very good, very good correction can be achieved the result of quick)

对特征值进行非极大值抑制的角点检测，并且选用了合适的阈值加强检测效果(corner detection by non-maxima suppression of Eigenvalues and selected the appropriate threshold to enhance detection)

基于样本的纹理合成加速方法，MRF，基于Li-Yi Wei的论文。(Acceleration method based on texture synthesis samples, MRF, based on Li-Yi Wei of paper.)

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P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩 P0303：采用灰度变换的方法增强图像的对比度 P0304：直方图均匀化 P0305：模拟图像受高斯白噪声和椒盐噪声的影响 P0306：采用二维中值滤波函数medfilt2对受椒盐噪声干扰的图像滤波 P0307：采用MATLAB中的函数filter2对受噪声干扰的图像进行均值滤波 P0308：图像的自适应魏纳滤波 P0309：运用5种不同的梯度增强法进行图像锐化 P0310：图像的高通滤波和掩模处理 P0311：利用巴特沃斯（Butterworth）低通滤波器对受噪声干扰的图像进行平滑处理 P0312：利用巴特沃斯（Butterworth）高通滤波器对图像进行锐化处理 (P0301: digital image data matrix display and Fourier Transform P0302: two-dimensional discrete cosine transform image compression P0303: using gray transform method to enhance the contrast of the image P0304: histogram equalization P0305: Simulation images by white Gaussian noise and salt and pepper noise P0306: 2D median filtering function medfilt2 right by Salt and Pepper image noise filtering P0307: using MATLAB functions filter2 of noise images mean filtering P0308: Image Adaptive Filter Weiner P0309: use five different gradient Enhancement Act for image sharpening P0310: Images of the high-pass filtering and mask handling P0311: use Butterworth (Butterworth) low-pass filter on the noise in the image smoothing P0312: use Butterworth ( Butterworth) high-pass filter for image sharpening)

说明：  一个基于matlab的改进的灰度图像分水岭分割算法，该算法改进了普通的分水岭算法的过分割等问题，经过一系列处理可是分割结果更加准确。(Matlab based on gray-scale image of the improved watershed segmentation algorithm to improve the ordinary over-segmentation of watershed algorithm and so on, but after a series dealing with a more accurate segmentation results.)

说明：  在计算机视觉中，图像分割是将图像分成多个片段的过程。这使我们能够通过以比原始图像更简单的表示方式来更好地分析图像。一种用于分割图像的方法是阈值分割；也就是说，将强度值低于阈值的所有像素设置为背景值，而将高于阈值的其他像素设置为前景值。最简单的阈值处理形式是对所有像素使用全局阈值，而自适应阈值处理根据像素及其周围环境动态改变阈值。典型地，阈值处理从灰度图像开始，并输出二进制图像以清晰地描绘图像中的片段。在本实验中，我们开发了一种自适应阈值算法，并将其与更简单的算法进行了比较。 此外，我们还开发了逆运动学证明来将机械臂移动到给定的x，y，z坐标。这一证明涉及三种命名身份，并获得了对机械臂设计的更好理解。(Image threshold segmentation)

这是图象缩放的代码，对于学习图像的朋友应该有所帮助(This is the image scaling code for the study should help the image of a friend)