Ihomomorphic

说明：  sprites communication to windows in unix sys

图像处理中的多尺度分割程序，使用matlab开发环境(Image processing procedures for multiscale segmentation)

对图像进行细化，本实验的细化对象是一组指纹二值图。(Image refinement, the refinement of the experimental object is a set of fingerprint binary image.)

视觉注意力模型，寻找感兴趣区域，模仿人眼找出最感兴趣的区域，再找出第二感兴趣的区域，以此类推(Visual attention model to find the region of interest, to imitate the human eye to identify the most interesting region, and then find the second region of interest, and so on)

使用基于PCA+KNN算法实现的人脸识别，本算法的优点在于使用的是基于2DPCA的方法，计算时间更短，效率更高。(PCA+ KNN-based face recognition algorithm, the advantage of this algorithm is based on the use of 2DPCA method in calculating the time is even shorter, more efficient.)

图像修复程序，专门用于去除图片中大的物体。去除后的图像裂缝通过基于用户手动得到的掩模进行填充。(This project involved removing large objects from images. From a user-specified mask, small patches were duplicated until all remaining gaps were filled. )

说明：  对原始图像进行阈值分割，把金属图像分割出来，抠掉金属的图像(Threshold segmentation is applied to the original image, and the metal image is segmented to remove the metal image)

说明：  在图像恢复技术中，总变分最小化是一种以保存图像细节为目标的规整化复原方法。本算法基于总变分最小化的思想，采取交替最小化的精确迭代策略来对图像和点扩展函数同时进行恢复。实验表明，该算法在噪声水平较高的情况下仍能对图像进行稳健的恢复。(Total variation image restoration techniques is a goal to save the image detail regularization recovery method. Algorithm based on total variation minimization thinking, take the alternating minimization accurate iteration strategy to simultaneously restore the image and point spread function. The experiments show that the algorithm in the case of high noise levels can still robust recovery image.)

本matlab程序可生成低通滤波器，数字图像处理(The matlab program can generate low-pass filter, digital image processing)

　对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)