Parcial-II

图片极坐标转换,可实现极坐标转换，以及求傅里叶变换(Picture polar coordinate conversion, convert polar coordinates can be realized, as well as seeking the Fourier transform)

说明：  基础图像处理语言，RGB各图层提取，量化图像，lena典型案例代码。(Basic image processing language, RGB layer extraction, quantization image, Lena typical case code.)

均值滤波，高斯滤波，双边滤波以及求PSNR的基本算法(Mean filtering, Gaussian filtering, bilateral filtering and basic algorithms for PSNR of)

说明：  Halcon与C#联合编程（Halcon12）(Halcon and C# joint programming (Halcon 12))

纹理模式的LBP特征表示及分类原理：就是通过定义一个模板，对于原图像中的每个点，使用该模板进行操作，模板中心点近邻区域对应的图像象素值与中心位置对应的象素值进行比较，且对于不同位置的比较结果赋予不同的权值，从而，变换图像中对应点的值就由模板对应各位置的比较结果之权和表示。(LBP texture pattern feature representation and classification theory: that by defining a template for the original image of each point, use the template to operate, the template center of neighboring regions corresponding to the center of the image pixel values corresponding to the pixel value comparison, and the comparison results for different locations given different weights, and thus, changing the value of the image corresponding points on the template corresponding to each position by the comparison of the results of the right to and express.)

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)

图像纹理特征提取，包括分形维数，灰度游程长度，灰度共生矩阵等五种图像纹理特征。(To extract image texture features, including fractal dimension, length of gray-level run-length, gray level co-occurrence matrix and other five kinds of image texture features。)

7670 32F4程序 代码 适合STM32F4探索者(7670 32F4 program code suitable for STM32F4 Explorer)

编程实现LoG或Sobel算子，并利用该算子提取给定图像中的边缘；全局最优阀值和自适应阀值分割的工作原理，编程实现阀值分割算法。 (Programming LoG or Sobel operator, and using the edge of the operator to extract a given image global optimal threshold and adaptive threshold segmentation of the working principle of programming to achieve a threshold segmentation algorithm.)

对于传统去噪模型的大幅改进，之前的模型都会出现阶梯效应的现象，采取了新的模型对图像进行建模，有效改善了图像去噪图像修复等过程中引入的阶梯效应，而且一定程度上对于图像纹理的修复也有很大的作用(For significantly improve the traditional de-noising model, the model will appear before the phenomenon of the staircase effect, to take a new model for image modeling, effectively improved the staircase effect denoising image restoration process introduced, and to a certain extent for texture of repair also has a significant role)