iekfpf_demos

这是一个matlab环境下的关于图像频谱分析的源代码，内附图像。(This is a Matlab environment on the image spectrum analysis of source code, containing images.)

对视频中的几帧进行移动目标检测，着重标记出移动目标。(Moving targets are detected for several frames in the video, with emphasis on the moving target.)

说明：  图像采集，简单的c#联合halcon做ncc模板匹配的操作(Image acquisition, simple C# combined with Halcon to do NCC template matching operation)

Gaussian Kernel Density Estimation with Bounded Support

matlab图像处理，可以提取图像轮廓，提取效果好。(matlab image processing, image contour can be extracted, extraction effect.)

信息检索和自然语言处理中经常会使用这些参数:准确率（Precision）、召回率（Recall）以及综合评价指标（F1-Measure ） (These parameters are often used in information retri and natural language processing (Precision), recall rate (Recall), and comprehensive uation index (F1-Measure). )

3种不同的分水岭分割方法以及三种方法的比较(3 different methods of watershed segmentation and Comparison of Three Methods)

用SLM法降低PAPR的CCDF,调用SLM函数来实现，毕业设计很有用的源代码(SLM method used to reduce PAPR of the CCDF, call the SLM function to achieve graduation design of the source code is useful)

说明：  利用R语言编程实现高光谱遥感的随机森林分类(Random Forest Classification Based on Hyperspectral Remote Sensing Using R Language Programming)

针对CT 医学图像和MR I 医学图像成像特点, 提出了基于快速整数提升小波变换的融合方法。在CT 和 MR I 两幅医学图像配准的前提下, 利用提升小波变换把图像分解成低频和高频子图像, 对于小波变换后的高频 子图像, 选择区域标准差大的作为融合后的子图像 对于低频子图像, 采用加权融合, 最后进行小波逆变换, 得到 融合后的图像, 并对融合后图像用信息熵、平均梯度、相关系数的指标进行评价。实验结果表明, 基于快速整数提 升小波变换融合中, 小波高低频系数采用不同的规则能够取得更好的融合效果, 其轮廓清晰。该算法能够提升融 合后的医学图像信息量, 同时有效地保护图像的细节信息, 在执行时间和图像质量上均优于普通小波算法。(A imed at the characterist ics of CT andMR Imedical images, a new image fu sion al2 go rithm based on the fast in t lif t ing w avelet t ran sfo rm s is p ropo sed. Two o riginal images are decompo sed by the fast in t lif t ing w avelet t ran sfo rm s. The fu sion ru le based on the max imum standard deviat ion value variance is u sed to fu se the h igh f requency sub2image, w h ile a w eigh t2 ed average fu sed ru le is app lied by coeff icien t s of the low f requency. F inally, the fu sion image is recon st ructed fo r perfo rm ing inverse fast in t lif t ing w avelet t ran sfo rm s. The fu sion image is evaluated by en t ropy, average gradien t, and co rrelat ion coeff icien t s. Experimen tal resu lt show s that the fu sion image hasmo re info rmat ion than o riginal images and imp roves the quali2 ty of o riginal images. M eanw h ile, the fu sion image p ro tect s detail characterist ics of the image, thu s the real2t ime p rocess and image qualit ies are w ell than tha)