yundong-dexiaoqiu

图像的纹理分析应用实例,做图像处理的同志们可以参考一下哟(image texture analysis application examples and do image processing comrades can make reference to yo)

sift Algorithm made by David Lowe sift demo

说明：  该方法在传统的极化SAR滤波Lee方法上增加了自适应窗口处理以及滤波参数预估计等步骤，有效的提高了传统的滤波方法的抑制相干斑的能力，同时能够很好的保持极化SAR图像的极化散射特性。(in the traditional method of increasing polarization SAR Lee adaptive filtering window processing and pre-filtering parameters estimation step, effectively improve the traditional filter method of inhibiting the ability to spot coherent while being able to maintain a good polarization scattering characteristics of SAR images.)

说明：  logistic混沌映射图，可以得到对logistic混沌映射图和基于logistic对图像加密(Logistic chaotic map)

显示24位灰度图象，24位真彩色图像以及图像的转换(shows 24 gray-scale image, 24 true color images and image conversion)

matlab的GUI设计教程，希望对利用matlab设计GUI的用户带来一定的帮助(Matlab GUI design tutorial, I hope the use of MATLAB design GUI users to bring some help)

说明：  UNet最早发表在2015的MICCAI上，短短3年，引用量目前已经达到了4070，足以见得其影响力。而后成为大多做医疗影像语义分割任务的baseline，也启发了大量研究者去思考U型语义分割网络。而如今在自然影像理解方面，也有越来越多的语义分割和目标检测SOTA模型开始关注和使用U型结构，比如语义分割Discriminative Feature Network(DFN)(CVPR2018)，目标检测Feature Pyramid Networks for Object Detection(FPN)(CVPR 2017)等。(Its influence has reached 70% in 2015. Then it became the baseline that most of the medical image semantic segmentation tasks, and inspired a large number of researchers to think about the U-shaped semantic segmentation network. In the aspect of natural image understanding, more and more SOTA models of semantic segmentation and object detection begin to pay attention to and use U-shaped structure, such as semantic segmentation, discriminative feature network (DFN) (cvpr2018), feature pyramid networks for object detection (FPN) (CVPR 2017), etc.)

说明：  对于X光骨骼增强，利用拉普拉斯变换，灰度变换，高频滤波对其增强(For X-ray bone enhancement, Laplace transform, gray transform and high frequency filter are used to enhance it)

经典迭代直方图分离聚类算法，该聚类算法基于图像直方图，非常适合于多类目标分割，计算速度非常快(Classical iterative separation histogram clustering algorithm, the clustering algorithm based on image histogram, very suitable for many types of object segmentation, calculation of very fast)

opengl 导入obj以及纹理，并且读入mtl啦啦啦啦绿撒的发生大(opengl objfsdagfadgadsfgsa)