QGA

八种图像置乱方法：希尔伯特变换、采样置乱、ZIGZIG置乱、等等等等(Eight kinds of image scrambling method)

垂直投影算法。可以直接在matlab上跑(err)

压缩感知重建算法,利用压缩感知理论实现用较少的采样量恢复出高分辨率的图像信息(compressive sensing reconstruction algoriyhm)

对灰度图像或RGB图像，进行基于边缘检测和区域生长的图像分割技术(On grayscale images or RGB images, for edge detection and region growing-based Segmentation)

我做的课题的响应信号，做了响应的小波包能量分析，希望对大家有帮助(I do issue a response signal, so the response of the wavelet packet energy analysis, we want to help)

图像处理中常用到的二十多个基本算法的源代码，如图像变换、灰度变换、图像滤波、锐化、边缘检测、阈值分割、边界提取、边界跟踪等(Commonly used in image processing to more than twenty basic algorithm source code, such as image conversion, gray-scale transformation, image filtering, sharpening, edge detection, threshold segmentation, edge detection, boundary tracking)

用小波变换作为稀疏基，采取OMP算法将图像重建恢复，由于算法计算量大会导致成像时间过长，程序用改进的分块处理缩短了时间，(Wavelet transform as a sparse base, take OMP algorithms to restore the image reconstruction algorithm to calculate the General Assembly led to the long imaging time, the program using a modified block processing to shorten the time)

在自动化生产线VC开发的运动控制机器视觉程序，XYZ三个轴有PCI板卡控制，视频卡采集图像后经算法处理找到图像的点，VC控制步进电机到加胶位置加胶，在机器上运行每日点胶100000次无故障(VC development in automated production lines motion control machine vision program, XYZ three-axis control with a PCI card, video card capture images after processing algorithm to find the image of the point, VC controlled stepper motor to position plus plus glue glue on the machine run the daily dispensing 100,000 times without failure)

压缩感知CS——采用小波变换进行稀疏表示，高斯随机矩阵为观测矩阵，重构算法为OMP算法，对256*256的lena图处理，比较原图和OMP算法在不同采样比例(0.74、0.5、0.3)下的重构效果，并各运行50次，比较算法性能PSNR和每次的运行时间 (Compressed sensing CS- using wavelet transform as sparse representation, Gaussian random matrix as the observation matrix and OMP algorithm as the reconstruction algorithm. Compare lena figure and the reconstruction results using OMP algorithm at different sampling ratio (0.74,0.50.3),then each runs 50 times, compare the performance of PSNR and each running time)

陆文凯老师数字图像处理第二次作业，前景背景分割和前景区域面积计算(Wen-Kai Lu a teacher of digital image processing a second operation, the background segmentation and the prospects for the future size of the area calculation)