plsa

粒子滤波跟踪，还算不错的一个demo，调试验证可以通过(Particle filter tracking, fairly good one demo, debug and verify through)

MC算法实现CT医学图像的三维重建，面绘制技术(MC algorithm CT medical image reconstruction, surface rendering technology)

高动态图像(HDR)合成算法，多曝光图像的配准算法(High dynamic image (HDR) synthesis algorithm, multi-exposure image registration algorithm)

基于压缩感知理论的超分辨率重建 实用程序包含论文中的试验(Super-resolution reconstruction based on compressive sensing theory The software reproduces the experiments published in the paper)

传统的几种图像增强与去噪方法，包括直方图处理，灰度变换，滤波去噪等几类。细分为直方图均衡化，直方图规定化，灰度线性变换，中值滤波，维纳滤波，同态滤波(The traditional methods of image enhancement and denoising include histogram processing, grayscale transformation, filtering and denoising. Subdivided into histogram equalization, histogram specification, gray level linear transformation, median filtering, Wiener filtering, homomorphic filtering)

该源代码主要是利用bagging,adboosting等集成学习的方法进行图像融合处理，效果甚好！(The main source is the use of bagging, adboosting ensemble learning methods such as image fusion, the effect is very good!)

指纹图像增强，gabor滤波器，包括形态学分割，形态学细化，加窗短时傅里叶变换增强，方向图估计及平滑，纹线频率估计及平滑(Fingerprint image enhancement, gabor filters, normalization, equalization, morphological segmentation, morphological thinning, windowed short time Fourier transform enhanced estimates and smooth pattern, ridge frequency estimation and smoothing)

由于彩色图像提供了比灰度图像更为丰富的信息, 因此彩色图像处理正受到人们越来越多的关注。彩色图像分割是彩色图像处理的重要问题, 彩色图像分割可以看成是灰度图像分割技术在各种颜色空间上的应用, 为了使该领域的研究人员对当前各种彩色图像分割方法有较全面的了解, 因此对各种彩色图像分割方法进行了系统论述, 即先对各种颜色空间进行简单介绍, 然后对直方图阈值法、特征空间聚类、基于区域的方法、边缘检测、模糊方法、神经元网络、基于物理模型方法等主要的彩色图像分割技术进行综述, 并比较了它们的优缺点, 通过比较发现模糊技术由于能很好地表达和处理不确定性问题, 因此在彩色图像分割领域会有更广阔的应用前景。(colorful image segment)

采用Graph Cut算法进行multiple-label的图像分割，算法很完整，非常适合初学者以及开发人员参考(multiple-label image segmentation using Graph Cut based algorithm, suitable for beginners and developers)

cordic matlab simulation algorithm, Accuracy can reach 98%, Is the topic of the elementary school stage curriculum design.