Mathematicauser

matlab课程设计，基于matlab的图像处理课程设计(matlab)

MUSIC算法的仿真，对于分辨空间多目标可以有何不错的效果(MUSIC algorithm simulation, the spatial resolution multi-objective what good results can be)

deeccccc a new version

黄锷论文中EMD和HHT的源程序，已经打包压缩,解压后可以使用(Wong Ngok paper on EMD and HHT source, has been packaged compression, decompression can be used after)

说明：  倒立摆实验，有关大学现代控制理论中的实验内容(Inverted pendulum experiment)

rake接收，walsh码直接扩频，三种分集合并方式(rake receiver, walsh code direct spread spectrum, three kinds of collection and methods)

图像处理PPT，适合初学者，介绍各种图像处理方法(Image processing PPT, suitable for beginners, introducing the various image processing methods)

用于对全景镜头进行标定，能求解出图像上对应点的世界坐标的方向向量(The OcamCalib Toolbox for Matlab allows the user (also inexpert users) to calibrate any central omnidirectional camera, that is, any panoramic camera having a single effective viewpoint (see section 17). The Toolbox implements the procedure initially described in the paper(Scaramuzza, D., Martinelli, A. and Siegwart, R., (2006). "A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion", Proceedings of IEEE International Conference of Vision Systems (ICVS 06), New York, January 5-7, 2006.) and later extended in (Scaramuzza, D., Martinelli, A. and Siegwart, R., (2006). "A Toolbox for Easy Calibrating Omnidirectional Cameras", Proceedings to IEEE International Conference on Intelligent Robots and Systems (IROS 2006), Beijing China, October 7-15, 2006. ). A detailed introduction to this model is in section 19 of this Tutorial. Furthermore, you can also see a demo of how the toolbox works here. The Toolbox permits the user to easily and quickly cal)

MATLAB6.0数学手册,很不错的一本参考手册，包括大部分工具箱函数注释。(MATLAB6.0 Math Handbook, it is a good reference manual, including most Toolbox Notes function.)

提出了一种基于小波变换和模糊集的图像融合算法.其基本思想是: 首先对图像进行小波变换,获得图 像的低频和高频分量 随后在融合过程中, 对低频和高频分量采取不同的融合策略, 即对低频分量采用平均能 量法进行融合,对高频成分利用图像的模糊集, 寻求一个模糊隶属函数作为融合算子进行融合 最后再对融合 后的图像进行小波反变换,重构出融合后的图像.实验结果证明了方法的有效性.(Proposed image fusion algorithm based on wavelet transform and fuzzy sets. The basic idea is: First the image wavelet transform to obtain the low and high frequency components of the image followed by low and high frequency components in the fusion process to take a different the integration of strategy, integration of the low frequency components using the average energy method, the use of high frequency components of the image fuzzy sets, look for a fuzzy membership function as a fusion operator for fusion image fusion wavelet transform and re- structure of fused images. experimental results demonstrate the effectiveness of the method.)