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图像的纹理分析应用实例,主要可用于模式识别当中(image texture analysis application, which can be used for pattern recognition)

动态的模拟天空中的云效果，速度特别流畅。(Dynamic simulation of the effect of cloud in the sky, the speed is very smooth.)

LTE中速率匹配的代码，包括子块交织，比特搜集，比特选择和修剪(The code rate matching in LTE, including the sub-block interleaving and bit gather, bit selection and pruning)

图像去雾c++版源代码，实现效果还不错，可直接运行。(Fog to remove the c++ version of the source code, the effect is not bad, can be run directly.)

该上传的256张CT图片是高质量的DICOME格式人类头骨的连续序列切片图，可直接用于医学三维重建或体绘制。(The upload of 256 CT images are of high quality DICOME form a continuous sequence of the human skull slice diagram can be directly used in medical 3D reconstruction or volume rendering.)

说明：  基于图像变换的火炮身管膛线参数检测技术研究(Based on image transform the Gun Barrel rifling parameter detection technology)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)

多径条件下基于加权空间平滑的阵元幅相误差校正(Multipath based on weighted spatial smoothing array element amplitude and phase error correction)

利用回转窑生产氧化铝的工艺中，提出了一种新的基于SVR（支持向量回归）的烧成带温度软测量方法。即首先对从回转窑采集到的烧结图像进行预处理，消除噪声的干扰；然后利用大津方法分割出物料区和火焰区，并提取这些区域的图像特征；其次利用基于SVR方法建立的烧成带温度模型计算温度值；参数计算.(The use of alumina rotary kiln production process, a new-based SVR (support vector regression) of the burning zone temperature soft measurement method. That is first collected from the rotary kiln sintering image pre-processing to eliminate noise interference Otsu method and then use the materials division of the district and flame zones, and extraction of image features in these regions SVR-based method followed by the establishment of the burning zone temperature model temperature parameters.)

中科院图像理解与计算机视觉课件6 值得参考一下 some topics on pattern recognition and computer vision(Chinese Academy of Sciences and Computer Vision Image Understanding Courseware 6 worth refer to some topics on pattern recognition and computer vision)