omp

关于脆弱性水印的，是一个挺不错的。希望能帮助到有需要的同学(on vulnerability watermark is a quite good. Intend to help the needy students)

内置虑镜功能，包括获取图像的属性，锐化，模糊，浮雕等功能． 可以缩放，优化图片．打开图片带预览功能,使用了gdiplus,能处理gif,bmp,jpg,png图片,处理速度也不错，呵呵,一直找图形格式转换的朋友就不需要东找西找了，它完全可以实现你的需求！ (Built-in lens into account features, including access to the properties of the image, sharpen, blur, emboss and other functions. Can be scaled to optimize picture. Open the image with the preview function, use the gdiplus, can handle gif, bmp, jpg, png images, the processing speed is not bad, huh, huh, graphic format conversion has been looking for friends do not need to look east and west, and it can achieve your needs!)

matlab小波分解信号的几个源程序，包括小波分解，时频转换一级功率谱分析(Matlab wavelet decomposition of the signal source program, including several wavelet decomposition, time-frequency transition level 1 power spectrum analysis)

应用条件随机场进行图像分割 使用方法：将pydensecrf-py27或pydensecrf-py35重命名为pydensecrf，放入C:Program FilesAnaconda3Libsite-packages 运行：python inference.py im1.png anno1.png out.png(Renameing the file "pydensecrf-py27" or "pydensecrf-py35" to the new name "pydensecrf" Puting this file "pydensecrf" in this directory "C:Program FilesAnaconda3Libsite-packages" cd examples/ python inference.py im1.png anno1.png out.png)

图割算法 求图像的立体匹配问题 最大流最小割问题(graphcut stereomatching matlabcode)

The second generation bandelets [Peyr´ e and Mallat 2005c] is a orthogonal multiscale transform that is able to capture thegeometric content of images and surfaces.

一个很好用的bmp图像转protelPCB封装库，如果有需要在pcb中插入图像，汉字的朋友可以下载(bmp to protel99，it s a good tool，welcom to download)

压缩感知和超分辨率论文，关于如何将低分辨率的图像如何重建成高分辨率图像，很有用(compressed sensing and super resolution)

HBT实验，这个实验用来测量恒星的角直径。这个算法可以对实验进行仿真(HBT experiment, this experiment is used to measure the angular diameter of stars. This algorithm can simulate the experiment)

实现简单图像处理，包括256色转灰度图、Hough变换、Walsh变换、中值滤波、二值化变换、亮度增减、傅立叶变换、反色、取对数、取指数、图像平移、图像旋转、图像细化、图像缩放、图像镜像、均值滤波、对比度拉伸、拉普拉斯锐化（边缘检测）、方块编码、梯度锐化、灰度均衡、直方图均衡、离散余弦变换、维纳滤波处理、逆滤波处理、阈值变换、高斯平滑。(simple image processing, including color to grayscale 256, the Hough transform, Walsh transform, Median filtering, binary conversion, brightness changes, Fourier transform, and color-from the few to admit index, image shifting, image rotation, refined images, image scaling, image mirroring, mean filtering, contrast stretching, Laplacian sharpening (edge detection), block codes, Sharpening gradient, gray balance, histogram equalization, discrete cosine transform, Wiener filter, reverse filtering, threshold transform, Gaussian smoothing.)