cdd

该函数用来实现快速离散余弦变换。该函数利用2N点的快速付立叶变换来实现离散余弦变换(This function is used to implement fast discrete cosine transform. 2N points of the function using the fast Fourier transform to achieve the discrete cosine transform)

Unix系统下，小波包变换的实现源码实例，，当然，稍作改动也可用于windows系统下。 (Unix systems, the instance of the wavelet packet transform source, of course, some minor changes can also be used in the windows system.)

算法实现消除小面积的区域,保留面积大的区域.对去除小斑点很稳健.(Algorithm to achieve the elimination of small areas of the region to retain the large area of the region. For the removal of small spots very sound.)

一种有效的全景图拼合预处理算法.适用于图像的拼接。是论文！(An effective pre-processing algorithm together panorama. Splicing applied to images. Is a thesis!)

关于MC三维重建算法的二义性消除的文章，很好的消除了MC算法中的二义性(it s the article about Three-dimensional reconstruction algorithm to eliminate ambiguity in MC)

实现原始的JPEG图片编解码，不借助任何的第三方库，纯C++。(To achieve the original JPEG image decoding, without using any third-party libraries, pure C++.)

实现对灰度图像的哈夫曼编码，对于其他图像，也可以类似的完成。(Realize grayscale images of hoffmann coding, for other image, also can be similar to the finish.)

说明：  基于opencv的小面积区域的去除.可以去除面积小于指定面积的无兴趣区域.(Opencv-based small area of the region to remove. Can remove an area of less than the specified area is not interested in the region.)

一个经典的动态视频图像去隔行处理的源代码,能消除双场图像的场效应(A classic dynamic de-interlacing video processing source code, to eliminate dual-field image of the field-effect)

基于OPENCV的SIFT特征提取与匹配算法。包含完整的从图像高斯金字塔、DOG、空间极值点提取、关键点描述、KDtree匹配等关键步骤的全部函数实现，对全面深入理解Lowe的SIFT算法有莫大帮助。程序运行前须安装（1）OpenCV: http://opencvlibrary.sourceforge.net （2）SIFT: http://web.engr.oregonstate.edu/~hess/index.html，并配置其环境参数。(OPENCV the SIFT-based feature extraction and matching algorithm. Contains a complete Gaussian pyramid from the image, DOG, space extremum point extraction, description of key points, KDtree matching key step in the realization of the full function of the comprehensive and in-depth understanding of Lowe s SIFT algorithm of tremendous help. Program to run before the installation of (1) OpenCV: http://opencvlibrary.sourceforge.net (2) SIFT: http://web.engr.oregonstate.edu/ ~ hess/index.html, and configure the parameters of their environment.)