cal_mosaic

由于图像在经过一次 JPEG 压缩和双重 JPEG 压缩之后其 DCT 系数具有一定的相关性，通过对这种相关性进行分析，提出了一种基于 JPEG 图像双重压缩特性的图像篡改检测算法，并用此算法检测图像是否经过篡改和定位篡改区域。 (Since the image after a first JPEG compression JPEG compression and double its DCT coefficients having some relevance, by this correlation is analyzed, and an image based on JPEG image compression characteristic double tamper detection algorithm, and the algorithm used to detect whether the image been tampered with and locate the tampered areas.)

小波去噪,实现阈值小波去噪，并且含有frost去噪，并且输出信噪比(Wavelet denoising, to achieve the threshold wavelet denoising, denoising and contains frost, and the output signal to noise ratio)

利用matlab对已知多对控制点的情况下进行两张图像校正，该算法能够取得较好的结果(Using matlab to correct two images when multiple pairs of control points are known.The algorithm can get good results.)

基于核函数的SAR图像目标识别,利用KPCA对SAR图像进行特征提取(SAR image target recognition based on kernel function，Use KPCA SAR image feature extraction)

图像分割和分形图像编码，其中图像分割的算法较多，而其只是分形编码的一部分(Image segmentation and fractal image coding, in which larger image segmentation algorithm, and its just part of fractal coding)

分为行人检测，特征提取，行人跟踪三步，其中最主要的代码也是这个代码的中心是行人跟踪这一部分，我采用的是kalman滤波器进行行人下一帧位置的预测，可以很好的提高行人跟踪的鲁棒性，跟踪结果比较准确。(Into pedestrian detection, feature extraction, pedestrian tracking steps, which is the center of the main code of the code is pedestrian tracking this section, I kalman filter is used to predict the position of the next frame pedestrians, can be a good improvement pedestrian tracking robustness, tracking results more accurate.)

说明：  对图像进行纹理特征提取，有LBP，旋转不变lbp，统一lbp，小波特征提取等比较齐全的特征提取算法(Texture feature extraction of images, such as LBP, rotation invariant lbp, unified lbp, wavelet feature extraction and other relatively complete feature extraction algorithms)

LSD直线检测算法的原理、步骤、结果文字资料以及具体程序实现(The LSD line detection algorithm principle, the steps of text information as well as specific procedures to achieve)

视频目标跟踪中的人脸检测，包括文章加程序(Video target tracking in the face detection, including procedures for the article plus)

BPFA 算法用于图像去噪 详细的程序与说明(BPFA for image denoising)