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多传感器多目标跟踪技术研究，，主要研究多传感器多目标跟踪技术 (Multi-sensor multi-target tracking technology research, mainly multi-sensor multi-target tracking technology)

rcmc: 距离徙动算法.SAR多点目标成像算法。含主瓣宽度和积分旁瓣比的求解。(rcmc: range migration algorithm. SAR multi-point target imaging algorithms. Including the main lobe width and sidelobe ratio integral solving.)

双目立体匹配，使用SAD，SSD，NCC算法，比较多种常见算法的优劣，对其优化实现快速准确匹配。(Binocular stereo matching, the use of SAD, SSD, NCC algorithm, compare the merits of a variety of common algorithms, and its optimization to achieve fast and accurate matching)

首先通过多分辨率分解法提取高频边缘，然后分别对每层的高频边缘进行非线性插值得到新的高频边缘，接着对高频边缘进行高通滤波得到等强后的高频边缘，最后对增强后的高频边缘进行修正。再在对增强的图像进行对比度拉伸，从而达到增强的目的！(First of all, through the extraction of multi-resolution decomposition of high-frequency edge, and then were on the edge of each high-frequency non-linear interpolation to be the new high-frequency edge, and then the edge of the high-frequency high-pass filter to be strong, such as after the high-frequency edge, and finally on the brink of enhanced high-frequency be amended. Again in contrast enhanced image stretching, so as to achieve the purpose of enhancing!)

关于高光谱图像的图像处理技术，RX异常检测技术，代码功能强大，且代码注释很多，对学习很有帮助。(Hyperspectral image on image processing techniques, RX Anomaly Detection technology, powerful code feature, and many code comments, learning helpful.)

曲波变换程序代码，实现图像的曲波分解以及显示，可以去图像进行曲波去噪增强，对彩色图像空间模型转化后提取曲波信息(Qu Bo transform program code, and display the image decomposition Qu Bo, Qu Bo can go to image edge enhancement, color image space model for transforming information extracted after Qu Bo)

说明：  super resolution可实现 很多算法(a lot of super resolution algorithms can be realized)

区域生长法的图像分割，可以较好地提取脑部图像。(The region growing method can extract brain image well.)

将肿瘤图像中的肿瘤轮廓提取，将轮廓的矩阵输入到函数中，得到肿瘤的分维结果。(The tumor contour is extracted from the tumor image, and the matrix of the contour is input into the function to obtain the fractal dimension of the tumor.)

(l)小波分析理论在变形监测数据处理研究中的理论意义和实用价值 (2)小波阂值去噪和多分辨分析在变形监测信号分析中的应用 (3)在算法和图像处理方面的优越性 ((L) wavelet analysis theory in the study of deformation monitoring data processing theoretical significance and practical value (2) wavelet thresholding denoising and multi-resolution analysis in deformation monitoring signal analysis application (3) in the algorithm and image processing superiority )