ICAforImage

实现了车辆目标的背景建模、前景检测、阴影消除、车辆跟踪(Achieve a vehicle target background modeling, foreground detection, shadow elimination, vehicle tracking)

标定投影仪与摄像机之间的透视变换矩阵，将摄像机图像转换成投影仪视角下的图像(calibration and transformation between camera and projector)

说明：  用matlab编写的图像复原源代码，采用维纳滤波复原技术，可对模糊和加噪的图像实现精确复原。(Prepared using matlab source code image restoration using Wiener filter restoration technology, can be vague and processors realize accurate image noise resilience.)

ENVI中HDF5科学数据支持补丁,更新为一个SAV文件 ,放在安装目录的save_add文件 夹下，启动ENVI即可使用。(HDF5 scientific data in support of ENVI patches, updates to a SAV file on the installation directory save_add folder, start ENVI can be used.)

提出了一种结合USFFT Curvelet 变换的各向异性扩散图像去噪模型。它有机结合了Curvelet 变换和各向 异性扩散（P-M扩散）两者的优点。通过P-范数方法选择合适的梯度阈值K，P-M扩散过程通过处理经过Curvelet 变换得到的图像的不同尺度的Curvelet 系数矩阵，实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。 实验表明，新模型的处理结果能有效避免传统P-M 扩散出现的阶梯效应，同时更好地保留图像的纹理和细节。 关键词：图像去噪算法；各向异性扩散；Curvelet 变换；P-M 扩散(Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed, which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively and keep the textures and details of images better.)

基于kalman滤波的图像目标识别的matlab代码，将运动目标从背景中分离出来(Kalman filter based on image recognition of matlab code, will be moving targets separated from the background)

采用最大方差阈值分割法，对指纹进行提取。(Using the maximum variance threshold segmentation method for fingerprint extraction.)

说明：  次文件夹包含两个程序，可以对振动信号进行包络分析，适合信号处理入门的朋友(do envelope analysis on vibration signal)

图像处理源程序，实现二值化变换，经一幅图像灰度化后，变成二值化图像，包括大津法、最大类间方差法、一般阈值法、及文本识别最有用的Niblack法(Image processing program and realized binarization transformation, after by a gray-scale image into binary image, including the Otsu method, Otsu method, the general threshold, and text to identify the most useful Niblack method)

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)