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matlab编写的对二值图像的数字水印添加与提取程序。压缩包中有示例图片。可以添加水印，结果肉眼不易分辨出变化，不影响使用。可加入信息长度达100个字节。提取时可验证是否被修改过，如未修改，可提取隐藏信息。当有修改发生时，可以定位修改的位置，并在图上标出。标识面积占修改面积的75％，一般修改都能标出(matlab prepared binary image of the digital watermark added and extraction procedures. Compression package has sample images. Can add watermarks, the results of the changes are not easily distinguishable from the naked eye, does not affect use. Can be added to the information length of 100 bytes. Verifiable extraction has been modified, if modified, can extract hidden information. When a modification occurs, you can modify the location of positioning and marked maps. Logo area accounted for 75 to amend the area generally can be identified modifications)

解薛定谔方程，通过辛几何算法得到的辛格式(Solving the Schrodinger equation by symplectic algorithm Singh style)

SSDA序贯相似性检测方法对图像进行模板匹配。从源图像中取小图，再到源图像中找到小图所处的位置。(SSDA sequential similarity detection method of the image template matching. Source image taken from the small map, to find a small map the source image position.)

图像基本算法研究，具有一定的参考价值,供大家参考(Image basic algorithm research, has a certain reference value for your reference)

说明：  对局部放电进行小波变换模式识别，解决放电破坏设备问题(Wavelet Transform Pattern Recognition for Partial Discharge)

彩色图像分割算法，首先基于直方图粗分，而后通过kmeans细分，得到分割结果(Color image segmentation algorithm, first, rough segmentation based on histogram and then broken down by kmeans get segmentation results)

这是一个比较完整的KPCA算法，通过这个算法可以快速的找到主要的特征向量进行主成分分析。(This is a relatively complete KPCA algorithm, this algorithm can quickly find the main feature vector principal component analysis.)

matlab代码实现meanshift图像分割算法，有较好的效果(matlab code meanshift realize image segmentation algorithm has better results)

最完整的CCA典型相关分析程序，分析两幅图像，相似度，匹配，融合都可以使用，分析天气变量也可以使用。(The most complete CCA canonical correlation analysis program, analysis of two images, similarity, matching, fusion can be used, analysis of weather variables can also be used.)

水平集边缘检测代码，利用了变分法进行优化和处理，实现了图像的快速边缘检测(Level set edge detection code is optimized and processed by using variational method, and fast edge detection of image is realized.)