inverse-with-Calibration-parameters

说明：  Calculate the Laplacian of an image, can be accelerated by the GPU.

sift图像处理的一个测试的代码，他是用C++写的 用到了opencv中的一些函数(sift image processing as a test of the code, he wrote with C++ uses some of the opencv function)

拐点的检测，对一个图像的拐点进行检测，使用的是freeman链码的方法，检测图像中拐点的方向，确定该方向是不是拐点。(Inflection point detection, an image of the inflection point for testing, use freeman chain code method, testing the image in the direction of the inflection point, we determine the direction is inflection point. )

说明：  利用BP神经网络进行图像分割。主要适用于RGB信息丰富的图像。以RGB为BP网络的三个输入，与对应的灰度图对网络进行训练。(The use of BP neural network image segmentation. RGB is mainly applied to information-rich images. BP network to RGB for the three inputs, with grayscale corresponds to the network training.)

说明：  直方图均衡化的一个程序，只能对BMP的黑白图像进行直方图均衡化(A histogram equalization process, only black and white BMP image histogram equalization)

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：  SAR影像单视数据转为多视数据，数据间相互转化，快捷处理SAR数据(Single-look SAR image data into a more visual data, data inter-conversion, fast processing SAR data)

本文主要介绍遗传算法的基本理论，叙述遗传算法在图像增强的的主要应用，即将原始图像变得更加清晰，特征变得更加明显。 现今关于图像增强的算法有很多，而这些算法大多是基于退化函数或者点扩展函数的知识进行图像处理的。当图像出现模糊或噪声影响大时，设计出的图像清晰化的效果肯定不够理想，因此有必要对图像进行增强处理。于是，可利用到遗传算法这种成熟稳定的仿生物进化的全局寻优算法，进行图像增强，由于遗传算法控制参数少、自适应度高，将选择该方法对图像退化分别进行不同的清晰化处理. 这样既增强了图像的对比度,又克服了传统直方图均衡化处理所造成的灰度级损失等缺点。 通过实验去表明，遗传算法从全局寻优的角度出发，能够较为精确地估计退化系统函数。和传统的线性增强、直方图均衡进行比较。实验结果表明该方法能改善原图像视觉效果，便于之后的图像分析。 (This paper mainly introduces the basic theory of genetic algorithm, genetic algorithm (ga) in the main application of image enhancement, the original image is more clear, characteristic becomes more obvious. Today about the image enhancement algorithm are many, and most of these algorithms is based on the degradation function or the knowledge of the point spread function of image processing. When the image appears fuzzy or noise influence, designed the image clarity of effect must not ideal, therefore it is necessary to enhance the image. Then, genetic algorithm is available to the mature and stable evolution of the global optimization algorithm, for image enhancement, due to less genetic algorithm control parameters, since the high fitness, will choose the method of image degradation, respectively, to manipulate the different motivation. It can enhance the image contrast, and overcome the traditional histogram equalization processing grayscale loss caused by the faults. Throug)

该代码是对图像进行二值化处理，进行图像分割(The code is to binarize the image, the image segmentation)

基于局部能量与模糊逻辑的红外偏振图像融合，该文与小波包，支持向量机等融合算法进行对比分析，说明该文算法的优势。(Infrared polarization image fusion based on local energy and fuzzy logic, this paper, wavelet packet, support vector machines and other fusion algorithm comparison analysis to illustrate the advantages of the proposed algorithm.)