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用matlab中各种不同方法对模糊图像进行复原，有维纳滤波，盲返卷积，Lucy-richardson方法，规则化复原图像等(Various different methods using matlab fuzzy image restoration, with Wiener filtering, blind convolution back, Lucy-richardson methods, rules-based recovery images, etc.)

红外图像细节增强仿真，其中使用双边滤波器进行图像分层。带测试源数据。(Infrared image detail enhancement, with test source data)

说明：  模拟退火算法在图像处理中的典型应用，用matlab编程(Simulated annealing algorithm in a typical image processing applications, programming with matlab)

使用echat 绘制的地图 百度地图api(Map drawn using echat baidu map api)

说明：  结构光光平面标定源码，注释详细，求出光平面在相机坐标系中的相对位置。(Structured light plane calibration source code, detailed comments, find the relative position of the light plane in the camera coordinate system.)

说明：  红外图像细节增强仿真，其中使用双边滤波器进行图像分层。带测试源数据。(Infrared image detail enhancement, with test source data)

利用MATLAB软件完成基于离散余弦变换（DCT）的可见水印算法，实现可见水印的嵌入(discussed the mathematical manipulation method of visible digital watermark and realized the visible digital watermarking inserting by completing the watermark algorithm，which based discrete cosine transformation (DCT) with the MATLAB software)

关于车辆跟踪的c++程序，使用了opencv进行跟踪，采用了帧差方法效果还不错(vehicle detection)

2019最新的神经网络隐写分析网络，对空域频域均可(The newest neural network steganographic analysis network 2019 is applicable to both spatial and frequency domain)

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.)