digital-image-processing-gonzalez---solution-manu

针对镜头畸变失真模型，进行镜头畸变失真校正的小程序(Distortion model for lens distortion, lens distortion distortion correction for a small program)

matlab图像处理中经典图片，包括lena，baboon，等(MATLAB image processing classic pictures, including Lena, baboon, etc.)

说明：  傅里叶变换中的角谱衍射理论，GS算法实现(Angle spectrum diffraction theory in Fourier transform, Realization with GS algorithm)

VC.NET图象处理,采用基于CImage类的图象处理技术,封装的函数为基本的图象处理部分,如几何变换等等,开发环境为VC++.NET(VC.NET image processing, based on CImage kind of image processing technology, Packaging for the basic functions of image processing, such as geometric transformation, and so on, the environment for the development of the VC.NET)

说明：  kl变换. KL变换的流程如下： （1)获取多幅图像的统计特性：图像之间的协方差 （2)获取协方差的特征值和特征向量，从而获取正交核:特征矩阵 （3)图像对应象素点对各个特征向量进行投影运算。(kl transformation)

用matlab写的一个将人脸图像进行归一化处理的程序，主要是将多个图像的尺寸进行调整使其大小一致。(Matlab write a face image the normalization processing program, mainly to adjust the size of multiple images to make it the same size.)

采用了Harrtraining和离子滤波算法实现了拥挤人群人头计数，非常有用。VC++和Opencv开发，采用Oepncv中的Harrtraining训练一个分类器即可运行(Human detection and tracking in high density crowds is an unsolved problem. Standard preprocessing techniques such as background modeling fail when most of the scene is in motion. We integrate human detection and tracking into a single framework, and in- troduce a conrmation-by-classication method to estimate condence in a tracked trajectory, track humans through occlusions, and eliminate false positive detections.)

基于分片重排列技术的维数约简方法，用于特征提取。(Patch Alignment for Dimensionality Reduction，IEEETrans.，2009.)

请采用学过的图像去噪方法（鼓励自己研究新算法），对Circuit_noise.jpg 、boy_noisy.gif（周期噪声） 和california_22_13.bmp图像进行去噪处理。(Please use learned denoising method (to encourage their study new algorithm), to Circuit_noise.jpg, boy_noisy.gif (periodic noise) and california_22_13.bmp image de-noising.)

遗传算法+FCM 用于SAR图像分类问题中，讲图分为两类或者三类~~~~~~~~~。(Genetic algorithm is used to SAR+ FCM image classification problem, speak figure divided into two classes or three kinds of ~ ~ ~ ~ ~ ~ ~ ~ ~.)