实现图像去噪功能 KSVD

Jsteg算法实现，Jsteg是一种基于JPEG的常用信息隐藏算法步骤如下: 首先，把掩体图像分为不重叠的8*8的子块，对每一子块进行DCT并对变换得到的DCT系数进行量化 其次，将待隐藏的信息进行加密，将加密结果嵌入到量化后值不为0，1或-1的DCT系数的最 低有效位(LSB)中，其嵌入顺序是按zigzag扫描顺序进行的。最后，用JPEG的嫡编码(包括哈夫曼编码，游程编码及DPCM)对嵌入秘密信息后的每一子块进行编码，从而得到一个含有秘密信息的JPEG stego文件。(Jsteg Algorithm)

SVM实现数据分类，可自行选取核函数，用于图像分割操作。程序可自动训练分类平面。(SVM for data classification, are free to select the kernel function，For image segmentation operation. The program can automatically train classifiers plane.)

实时统计监控视频下路人人数，采用python(This is a demo made for tracking pedestrian)

基于AR2模型的粒子滤波源代码，可用于图像处理，视觉跟踪，希望可以帮助有需要的人(AR2 model particle filter based on source code can be used for image processing, visual tracking, I hope to help people in need)

自己写的计算一副图像重心的小程序，绝对有用。(Write their own calculation of an image center of gravity of small procedures, absolutely useful.)

一种求解电大平台天线互耦的时域积分方程快速算法(Solving the Antenna TV platform stie fast algorithm)

说明：  

一种自适应chirplet分解的快速算法 针对信号自适应chirplet分解未知参数多、实现起来比较困难的特点，文献[1]提出了一种新的chirplet分解快速算法。该算法利用计算信号的二次相位函数，得到其能量分布集中于信号的调频率曲线上的结论，此时通过谱峰检测可同时获得chirplet调频率、时间中心和幅度的估计；然后通过解线性调频技术获得其初始频率和宽度的估计，仿真结果验证了本文算法的有效性。 (Chirplet an adaptive decomposition algorithm for rapid adaptive signal decomposition Chirplet many unknown parameters, is more difficult to achieve the characteristics of the literature [1] proposed a new fast algorithm Chirplet decomposition. The algorithm calculating the signal function of the second phase, its energy distribution to be concentrated in the signal modulation frequency curve on the conclusions, this time through the spectral peak detection can be obtained simultaneously Chirplet tune the frequency, timing and magnitude of the estimated center then through the solution line technology of FM frequency and the width of the initial estimates, the simulation results verify the effectiveness of the algorithm.)

说明：  几种常用的SAR图像滤波程序：初值滤波、中值滤波、维纳滤波、Lee滤波、kuan滤波等(some common filter program of SAR image,such as Lee filter,kuan filter.)

老外写的程序，可对三角形进行渲染，有详细的算法介绍。非常棒(A good Triangle Renderer Project，with detailed introduction.)