Registration

说明：  几个白平衡程序，都能运行出来，可以用于水下图像偏绿偏蓝现象的颜色调整(Several white balance programs can be run)

在大图中找小图

28个vc++图像处理原程序之--对比度拉伸(28 vc++ Image processing of the original procedure- contrast stretching)

ostu二值化算法vc实现，基于MIL图像处理软件包将图像解析，通过ostu求取二值化阈值，实现二值化算法(ostu binarization algorithm to achieve vc, MIL image processing software package based on the image resolution, strike through ostu binarization threshold binarization algorithm to achieve)

Image retrieval lecture

利用经典PM模型在matlab上运行的图像降噪程序(Image denoising program based on classical PM model)

提取图像的lbp纹理特征，然后进行向量表示( Lbp extracted texture features of the image, and then vector representation)

说明：  对3D数据运用gpu实现八叉树，完成分割并进行渲染。(The use of 3D data on the GPU octree to achieve complete segmentation and rendering.)

在HSV色彩空间进行彩色图像分割源码，包括学习和训练算法，获得分割参数(In the HSV color space for color image segmentation source code, including learning and training algorithm, access to segmentation parameters)

这本书提供了充分的代表性逆合成孔径雷达（ISAR）成像，这是一种流行和重要的雷达信号处理工具。本书涵盖了所有可能的ISAR成像方面。这本书提供了一个介绍了专家组的逆问题和合成孔径雷达（SAR）提出的问题之前，信号处理技术和雷达基本相当。如高分辨率SAR的重要概念，脉冲压缩和图像形成连同相关的MATLAB代码。 ISAR成像的基本原理后，这本书提供了相关的MATLAB函数和代码成像ISAR成像的详细程序。 ISAR成像，多个成像技巧和微调，如零填充和窗口程序，以提高图像的质量也被提出。最后，逆合成孔径雷达图像中的各种实际应用，如成像天线平台散射的，是在单独的一章。所有这些算法，MATLAB代码和数字都包括在内。最后一章考虑了在ISAR成像的先进理念和发展趋势。(This book provides a full representation of Inverse Synthetic Aperture Radar (ISAR) imagery, which is a popular and important radar signal processing tool. The book covers all possible aspects of ISAR imaging. The book offers a fair amount of signal processing techniques and radar basics before introducing the inverse problem of ISAR and the forward problem of Synthetic Aperture Radar (SAR). Important concepts of SAR such as resolution, pulse compression and image formation are given together with associated MATLAB codes. After providing the fundamentals for ISAR imaging, the book gives the detailed imaging procedures for ISAR imaging with associated MATLAB functions and codes. To enhance the image quality in ISAR imaging, several imaging tricks and fine-tuning procedures such as zero-padding and windowing are also presented. Finally, various real applications of ISAR imagery, like imaging the antenna-platform scattering, are given in a separate chapter. For all these algorithms, MATLA)