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基于视频的车道线检测,首先对视频进行一系列预处理，然后进行边缘检测，霍夫变换直线检测，最后对检测出来的直线进行非车道线排除。(Video-based lane detection, the first of a series of video preprocessing, edge detection and Hough transform line detection, finally detected non-linear lane excluded.)

另一款BP/TP使用的SVGA图形模式程序。效果也不错(Another BP/TP use SVGA graphics mode procedures. The results would be good)

利用GPU加速的SIFT算法，实现影像匹配，并利用RANSAC进行粗差的剔除(GPU-accelerated use SIFT algorithm to achieve image matching, and use RANSAC removing coarse poor)

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.)

SAR影像cloude分解，提取极化信息(PolSAR cloude decomposition)

水平百叶窗显示图片，讲一张图像垂直分成若干份，bitblt一行一行的显示(The level of blinds show pictures, talk about an image vertically divided into several copies, bitblt display line by line)

说明：  边缘检测算法 速度快 你一定会满意的。以前是要收费的。现在免费给你们。 源码经过测试真确无误。 (edge detection algorithm faster you will surely satisfied. Prior to the charges. Now free to you. Source tested truthful.)

图像噪点检测，去除难以区分的斑点噪声及平滑图像 双曲型差分(Image denoising and hyperbolic difference)

说明：  小波应用于图像融合的程序，选择的是5层小波分解(applied wavelet image fusion procedures, the choice is a five-storey wavelet decomposition)

BLS-GSM 即"Bayesian Least Squares - Gaussian Scale Mixture".基于贝叶斯最小平方-高斯概率混合模型的算法。用于图像去噪。相关文献索引详见readme(BLS-GSM or )