huiduzhifang

rice大学CHOI写的一个关于小波域HMT模型的图像去噪算法。算法比较经典。对研究HMT模型的同行有很大参考价值。(rice university CHOI written on wavelet-domain HMT model for image denoising algorithm. Comparison of the classical algorithm. HMT model of research has great reference value counterparts.)

说明：  sift算法实现的图像匹配程序，使用matlab编写的，多用于图像拼接，融合等领域。(The image matching program implemented by SIFT algorithm is written by MATLAB, and it is mostly used in image splicing, fusion and other fields.)

EM算法是最为经典的统计图像分割方法，代码基于matlab，使用EM算法实现图像分割,源代码加实例图像，非常好用(By using EM algrithm to realize the segementation of image)

利用霍夫变换检测直线，园，椭圆，曲线，简单有效，用用方便(Using Hough transform to detect straight lines, park, oval, curve, simple, effective, easy to use with)

KRUSAL算法实现最小生成数的 最小生成数的 最小生成数的(The KRUSAL algorithm realizes the minimum generating number of the minimum generating numbe)

SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点，其匹配能力较强，可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题，甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力。该算法目前外文资料较多，但中文方面的介绍较少.(SIFT feature matching algorithm is at home and abroad feature points matching hot area of ​ ​ research and difficulties in its matching capability that can handle between the two images, translation, rotation, the matching problem in the case of affine transformation, and even to some extent have a relatively stable feature of the ability to match images taken on any angle. The algorithm is more foreign materials, but the Chinese introduction less.)

改进后的非线性各向异性扩散用于图像中的保边去噪，增加了二阶导数，是滤波效果更好(Improved nonlinear anisotropic diffusion for edge preserving image denoising, an increase of second derivative, is a better filtering effect)

一种基于小波分析的彩色图像融合方法，需要同一场景的红外与夜视各一张，同时选取任意场景合适的彩色照片作为参考图像(A color image fusion method based on wavelet analysis, infrared and night vision needs each one of the same scene, the scene at the same time any suitable color photo as a reference image)

本算法需要两幅或多幅不同偏振角度的有雾图像，应用暗通道算法估计大气光强，最终所得的图像去雾效果较好(Fog fog removal based on polarization information)

建立了混合高斯模型，可以对静止背景下运动目标进行检测。(Gaussian mixture model is established, you can still detect moving target in the background.)