c_tuxing

本代码可以实现图像的维纳滤波，经过调试无错误，对于学习图像处理有较好帮助。(This code can achieve the image filtering, error-free through the debugging, better for learning image processing help.)

实现对酒瓶子的边缘检测，背景差分，垂直和水平投影等，并可实现计数功能。(Achieve the bottles of edge detection, background difference, the vertical and horizontal projection, and to achieve counting.)

数字图像处理方面的常用操作 人脸识别 图像打开和保存 类似photoshop操作 (Digital image processing operations commonly used face recognition and preservation of the image to open a similar operation photoshop)

说明：  ：针对显微图像分析、识别需要的全自动控制显微镜，研究开发其相应的图像处理算法。提 出了能量谱自动聚焦评价函数算法、自适应选取基准图的图像拼接算法、改进 Laplacian算子的多层 聚焦图像叠合算法等。该算法模块已成功地应用于所开发的CMIAS 显微医学图像分析系统中，取得 了满意的应用效果。(【ABSTRACT】For the automatic microscope required by micro-image analysis and recognition, the relevant image processing a lgorithms are investigated. Three algorithms are described: energy-spectrum image auto focusing evaluation function, image merging based on the adaptive selection of standard image and sum-modified-Laplacian (SML) operator for multi-focus image fusion. The algorithms have been applied successfully to CMIAS medical micro-optical image analysis system and testified to be feasible and effective. )

说明：  MFC结合VTK做图像处理的程序，实现了图像的显示和缩放功能。(MFC combines VTK to do image processing procedures, to achieve an image display and the zoom feature.)

二维图形图像处理，高斯平滑的源代码，图像预处理(Two-dimensional graphic image processing, Gaussian smoothing of the source code, image preprocessing)

kmeans算法实现，对图像处理。亲自使用过，可用，供参考。(Kmeans algorithm for image processing.)

说明：  该书介绍的用VC实现图像处理，其中包括一些图像处理知识的介绍(The book described the realization of image processing using VC, including some knowledge of image processing introduction)

平台基于visual studio2015，使用opencv函数实现双边滤波，进行图像处理(bilateral Filter based on opencv)

说明：  傅立叶变换在图像处理中的重要作用： (A) 图像增强与图像去噪 绝大部分噪音都是图像的高频分量，通过低通滤波器来滤除高频噪声；边缘也是图像的高频分量，可以通过添加高频分量来增强原始图像的边缘； (B) 图像分割与边缘检测 提取图像高频分量 (C) 图像特征提取 形状特征：傅里叶描述子 纹理特征：直接通过傅里叶系数来计算纹理特征 其他特征：将提取的特征值进行傅里叶变换来使特征具有平移、伸缩、旋转不变性 (D ) 图像压缩 可以直接通过傅里叶系数来压缩数据；常用的离散余弦变换是傅立叶变换的实变换； (Fourier transform in the important role of image processing: (A) image enhancement and image denoising Most of all images of high frequency noise by low pass filter to filter out high frequency noise edge is the image of the high frequency components can be enhanced by adding high frequency components to the edge of the original image (B) Image segmentation and edge detection High frequency components extracted image (C) image feature extraction Shape features: Fourier descriptors Texture: directly through the Fourier coefficients to calculate the texture features Other features: The characteristic value extracted by Fourier transform to the characteristics of translation, scaling, rotation invariance (D) image compression Fourier coefficients can be directly compressed data commonly used discrete cosine transform is the Fourier transform of the real transformation 朗读显示对应的拉丁字符的拼音)