luikun_v65

数字全息分区算法模拟，用于从一副同轴全息图中恢复出物体的像(digital holography)

对较真实的运动模糊图像进行恢复，此种运动模糊图像限于水平或垂直的运动模糊图像。 参考文献：Removing Camera Shake from a Single Image ,siggraph06(On the more realistic motion-blurred image restoration, such motion-blurred images limited to horizontal or vertical motion-blurred images. References: Removing Camera Shake from a Single Image, siggraph06)

医学图像分割是数字图像分析中的重要环节，是长期以来国内外研究的热点问题，本代码专注于血管图像领域的分割。(Medical image segmentation is an important part of digital image analysis, is a hot topic at home and abroad for a long time, this code is to focus on areas of blood vessel image segmentation method.)

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

说明：  matlab图像处理用于目标分割，分割后的图像在用形态学滤波处理(matlab image processing for object segmentation, image segmentation using morphological filtering deal)

设置位置断点跟踪程序，VC++精选编程源码，很好的参考资料。(Set breakpoint location tracking procedures, VC++ programming source code, a good reference.)

canny边缘检测，还有车道线检测。效果还可以。(canny edge detection, and lane detection. The effect can be.)

Matlab遥感道路提取之Hough检测(Matlab to extract the Hough detect remote road)

说明：  根据Itti视觉注意模型得到图像的显著区域。本算法简单并且对一般简单的图像能够提取出比较好的显著区域。(According to Itti visual attention model are significant regions in the image. The algorithm is simple and easy on the general good image to extract a significant area.)

说明：  PCA图像降噪新算法-LPG PCA，全名叫做Two-stage Image Denoising by Principal Component Analysis with Local Pixel Grouping。内含算法代码和数据集，均经本人实测，可进行灰度图像和RGB图像的降噪，且PSNR和SSIM指标明显好于小波滤波、K-SVD等经典算法。值得学习图像降噪的看看！(The new algorithm of PCA image denoising LPG PCA, full name is two stage image denoising by principal component analysis with local pixel grouping. The algorithm code and data set can be used to reduce the noise of gray image and RGB image, and the PSNR and SSIM are better than the classical algorithms such as wavelet filtering and K-SVD. It's worth learning about image denoising!)