prop

说明：  对有噪声的图像进行图像复原，通过迭代算法实现此功能(Image restoration for noisy images, this function is implemented by an iterative algorithm)

说明：  用于计算图像的空间频率和空间频率图（可看作是图像的轮廓）(Used to calculate the spatial frequency and spatial frequency graph of the image)

说明：  平台基于visual studio2015，使用opencv函数实现高斯滤波，进行图像处理(gaussian blur based on opencv)

针对电气设备同一场景的红外与可见光图像间一致特征难以提取和匹配的问题，提出了一种基于斜率一致性的配准方法。首先通过数学形态学方法分别提取红外与可见光图像的边缘，得到粗边缘图像；然后通过SURF算法提取两幅边缘图像的特征点，根据正确的匹配点对之间斜率一致性的先验知识，进行特征点匹配；最后通过最小二乘法求得仿射变换模型参数并实现两幅图像的配准。实验结果表明，该方法有效提高了匹配点对的正确率，能够对电气设备红外和可见光图像实现高精度的配准。(In this paper, a method based on slope consistency is proposed to solve the problem that the uniform features of infrared and visible images are difficult to extract and match. Firstly, the edges of infrared and visible images were extracted by mathematical morphology, and the rough edge images were obtained. Then, the feature points of two edge images were extracted by SURF algorithm, and the priori knowledge of slope consistency was obtained according to the correct matching point, and the feature points were matched. Finally, the model parameters of affine transformation are obtained by least square method and the registration of two images is realized. The experimental results show that this method can effectively improve the accuracy of matching points, and can realize high precision registration of infrared and visible images of electrical equipment.)

基于matlab的高分辨距离像的研究 svm实现(high ratio radar magic basic on matlab)

moire条纹图像处理程序，由matlab开发的实例。(Moire fringe image processing procedures developed by the matlab example.)

说明：  这个是数字图像处理的算法原理介绍，讲的非常仔细，很好，是中文版。冈萨雷斯出的大作(This is the principle of digital image processing algorithm, speak very carefully, very good, is the Chinese version. Gonzalez's masterpiece)

小波分辨边缘，但是要自己加工一下。可以读取RGB转化为灰度图像。(Wavelet-resolved edge, but to look at their own processing. RGB can be read into a gray image.)

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.)

一种新的水平集方法由Chunming Li教授开发的，还有配套的使用说明(A new level set method developed by Professor Chunming Li, as well as supporting the use)