Lee

图像分割中的分水岭算法实现--图像灰度变化--图像增强--多维图像(Watershed image segmentation algorithm image change image enhancement multi-dimensional image)

snake算法的c源代码,一般snake算法可以用于图像的边缘检测,是一种比较新的方法(snake algorithm c source code, the general snake algorithm can be used to image edge detection, is a relatively new approach)

对于低水平的视觉情况下，加权核规范最小化算法及其应用。(Weighted Nuclear Norm Minimization and Its Applications to Low Level Vision)

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.)

visionpro字符识别

时频分布处理（重排、图像的信息处理以及Winger-Hough变换）(Time-Frequency Distribution Processing (rearrangements, the image information processing and the Hough transform Winger))

将原始载体图片经过一维冗余离散小波变换分成四个子频带，分别对每个子频带进行奇异值分解， 将水印图片灰度值直接按比例缩小嵌入到奇异值矩阵中，再将此矩阵进行一次奇异值分解得到奇异值当做此子带的奇异值， 重建此子带矩阵，而后将进行反冗余离散小波变换得到嵌入载体后的水印图像。(The original image after the one-dimensional vector redundant discrete wavelet transform is divided into four subbands, respectively, of each sub-band for the singular value decomposition, the watermark image gray value scale down directly embedded into the matrix singular value, then this matrix is ​ ​ a Singular value decomposition singular value as the singular values ​ ​ of this sub-band, the reconstruction of this sub-band matrix and after anti-redundant discrete wavelet transform watermark image after embedding the carrier.)

曲面拟合法是一种高精度、计算量小、抗噪性能强的方法，当前已被广泛地应用于 各种场景。比如岩石材料的变形测量、电子器件变形的测量、基于掌纹图像相关匹 配的重复定位技术等。曲面拟合法能够成功计算出亚像素位移的前提是整像素搜索阶 段可以正确搜索出模板的整像素匹配点，一旦整像素匹配点搜索出现错误，那么亚像素 测量阶段所得到的位移距离就会失去意义。 使用不同的拟合函数对相关系数矩阵进行曲面拟合，会对结果产生一定的影响，比 较常用的拟合函数有二次函数、三次函数、高斯函数等。(Surface fitting method is a high-precision, computational complexity is small, strong anti-noise performance method, has been widely used in various scenes. For example, deformation measurement of rock materials, deformation measurement of electronic devices, and repetitive location technology based on palmprint image correlation matching. Surface fitting method can successfully calculate the sub-pixel displacement on the premise that the whole pixel search stage can correctly search the template of the whole pixel matching point, once the whole pixel matching point search error, then the sub-pixel measurement phase of the displacement distance will be meaningless. Using different fitting functions to fit the surface of the correlation coefficient matrix will have a certain impact on the results. The commonly used fitting functions are quadratic function, cubic function, Gaussian function and so on.)

改进的 SUSAN 算法，用于自适应阈值的边缘检测(improved algorithm for the adaptive thresholding edge detection)

focuss算法 关于图像稀疏性分解中字典学习的经典算法 和大家一同分享 (focuss algorithm on the sparse image decomposition in the dictionary of the classical learning algorithm and we share)