MRF

理解频域处理与空间域处理的等效关系与步骤，掌握频域相乘与空间域循环卷积之间的对等关系，理解DFT运算中补零的效果。(Understand the equivalent relationship and steps of frequency domain processing and space domain processing, understand the reciprocal relationship between frequency domain multiplication and space domain circular convolution, and understand the effect of zero padding in DFT operation.)

用于产生离散高斯函数的Matlab源代码。(Discrete Gaussian function used to produce the Matlab source code.)

用Matlab写的Bayer插值与白平衡算法，包含双线性和边缘检测两种插值算法以及White Patch自动白平衡算法(Bayer Interpolation and white balance algorithm implemented with matlab.)

采用半隐式方案实现变分水平集图像分割方法(Active contour without edge, image segmentation)

实现了Thien在他的文章《secret image sharing》中提出的（r，n）门限秘密图像分存方案。 (Thien in his article " secret image sharing" (r, n) Door Threshold Secret Image Sharing Scheme.)

PIVlab是一个开源的粒子图像测速（PIV）软件。它不仅能够通过图像对计算出速度，而且能够得到、显示和导出多个参数的流动模式。通过一个友好的图形用户界面（GUI），使得的PIV技术分析和数据后处理更加快速、高效。(PIVlab is an open-source particle image velocimetry (PIV) software. It can not only calculate the speed through the image pairs, but also can get, display and export the flow patterns of multiple parameters. Through a friendly graphical user interface (GUI), the PIV technology analysis and data post-processing are faster and more efficient.)

基于马尔科夫随机场的，例子学习超分辨率复原代码。(This is an implementation of the example-based super-resolution algorithm. Although the applications of MSFs have now extended beyond example-based super resolution and texture synthesis, it is still of great value to revisit this problem, especially to share the source code and examplar images with the research community. We hope that this software package can help to understand Markov random fields for low-level vision, and to create benchmark for super-resolution algorithms.)

基于小波阈值的去噪方法，可以通过改变不同的参数达到不同的效果。(Wavelet threshold de-noising method can achieve different effects by changing the different parameters.)

压缩感知重建算法，SPARSA算法，与大家一起交流(Compressed sensing reconstruction algorithm, sl0 algorithm exchanges, together with you)

可以快速准确的找出光斑、或者任何椭圆形状二值图像的质心(The center of mass of a two value image can be quickly and accurately identified.)