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sparse_fusion

于 2020-10-06 发布 文件大小:5202KB
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  运用最小二乘和一范数约束求解低分辨率多光谱图像和高分辨率全色图像融合成高分辨率多光谱图像，程序附带主流的图像融合评价标准，需要融合的图像，对比图像；以及附带程序所需的稀疏包(Using least squares and a norm constraint solving low-resolution multi-spectral image and panchromatic image fusion into a high-resolution multi-spectral images, the program comes with mainstream image fusion uation criteria require the integration of image contrast image and Sparse package comes with the program required)

文件列表：

sparse_fusion




.............\spams-matlab
.............\............\build
.............\............\.....\displayPatches.m,1296,2013-11-29
.............\............\.....\mexArchetypalAnalysis.m,406,2014-06-14
.............\............\.....\mexArchetypalAnalysis.mexw64,154112,2015-03-27
.............\............\.....\mexBayer.m,311,2012-05-20
.............\............\.....\mexBayer.mexw64,27136,2015-03-27
.............\............\.....\mexCalcAAt.m,381,2012-03-15
.............\............\.....\mexCalcAAt.mexw64,78336,2015-03-27
.............\............\.....\mexCalcXAt.m,414,2012-03-15
.............\............\.....\mexCalcXAt.mexw64,78848,2015-03-27
.............\............\.....\mexCalcXtY.m,267,2012-03-15
.............\............\.....\mexCalcXtY.mexw64,52736,2015-03-27
.............\............\.....\mexCalcXY.m,264,2012-03-15
.............\............\.....\mexCalcXY.mexw64,52736,2015-03-27
.............\............\.....\mexCalcXYt.m,267,2012-03-15
.............\............\.....\mexCalcXYt.mexw64,52736,2015-03-27
.............\............\.....\mexCD.m,2197,2012-03-15
.............\............\.....\mexCD.mexw64,105984,2015-03-27
.............\............\.....\mexCombinePatches.m,437,2014-05-19
.............\............\.....\mexCombinePatches.mexw64,66560,2015-03-27
.............\............\.....\mexConjGrad.m,559,2012-03-15
.............\............\.....\mexConjGrad.mexw64,55808,2015-03-27
.............\............\.....\mexConvFista.mexw64,828416,2015-03-27
.............\............\.....\mexConvFistaFlat.m,441,2014-05-19
.............\............\.....\mexCountConnexComponents.m,833,2012-05-20
.............\............\.....\mexCountConnexComponents.mexw64,65024,2015-03-27
.............\............\.....\mexCountPathsDAG.m,471,2012-05-20
.............\............\.....\mexCountPathsDAG.mexw64,62464,2015-03-27
.............\............\.....\mexDecompSimplex.m,338,2014-06-14
.............\............\.....\mexDecompSimplex.mexw64,123904,2015-03-27
.............\............\.....\mexEvalPathCoding.m,1930,2012-05-20
.............\............\.....\mexEvalPathCoding.mexw64,423424,2015-03-27
.............\............\.....\mexExtractPatches.m,304,2014-05-19
.............\............\.....\mexExtractPatches.mexw64,59392,2015-03-27
.............\............\.....\mexFistaFlat.m,6608,2014-06-16
.............\............\.....\mexFistaFlat.mexw64,833536,2015-03-27
.............\............\.....\mexFistaGraph.m,3608,2012-05-20
.............\............\.....\mexFistaGraph.mexw64,816128,2015-03-27
.............\............\.....\mexFistaPathCoding.m,3536,2012-05-20
.............\............\.....\mexFistaPathCoding.mexw64,814080,2015-03-27
.............\............\.....\mexFistaTree.m,3742,2012-05-20
.............\............\.....\mexFistaTree.mexw64,816640,2015-03-27
.............\............\.....\mexGraphOfGroupStruct.m,568,2013-06-24
.............\............\.....\mexGraphOfGroupStruct.mexw64,71680,2015-03-27
.............\............\.....\mexGroupStructOfString.m,1743,2013-06-24
.............\............\.....\mexGroupStructOfString.mexw64,52736,2015-03-27
.............\............\.....\mexIncrementalProx.m,2975,2013-12-04
.............\............\.....\mexIncrementalProx.mexw64,516096,2015-03-27
.............\............\.....\mexInvSym.m,221,2012-03-15
.............\............\.....\mexInvSym.mexw64,53248,2015-03-27
.............\............\.....\mexL1L2BCD.m,1913,2012-03-15
.............\............\.....\mexL1L2BCD.mexw64,92672,2015-03-27
.............\............\.....\mexLasso.m,2843,2012-05-18
.............\............\.....\mexLasso.mexw64,184832,2015-03-27
.............\............\.....\mexLassoMask.m,2367,2012-05-15
.............\............\.....\mexLassoMask.mexw64,146944,2015-03-27
.............\............\.....\mexLassoWeighted.m,2333,2012-03-15
.............\............\.....\mexLassoWeighted.mexw64,126464,2015-03-27
.............\............\.....\mexNormalize.m,249,2012-03-15
.............\............\.....\mexNormalize.mexw64,55296,2015-03-27
.............\............\.....\mexOMP.m,2380,2012-05-20
.............\............\.....\mexOMP.mexw64,125440,2015-03-27
.............\............\.....\mexOMPMask.m,2331,2012-05-20
.............\............\.....\mexOMPMask.mexw64,147456,2015-03-27
.............\............\.....\mexProximalFlat.m,4942,2012-07-20
.............\............\.....\mexProximalFlat.mexw64,545280,2015-03-27
.............\............\.....\mexProximalGraph.m,3397,2012-05-20
.............\............\.....\mexProximalGraph.mexw64,547328,2015-03-27
.............\............\.....\mexProximalPathCoding.m,2187,2012-05-20
.............\............\.....\mexProximalPathCoding.mexw64,546816,2015-03-27
.............\............\.....\mexProximalTree.m,5756,2012-06-13
.............\............\.....\mexProximalTree.mexw64,547840,2015-03-27
.............\............\.....\mexReadGroupStruct.m,1404,2013-06-24
.............\............\.....\mexReadGroupStruct.mexw64,65536,2015-03-27
.............\............\.....\mexRemoveCyclesGraph.m,881,2012-05-20
.............\............\.....\mexRemoveCyclesGraph.mexw64,67584,2015-03-27
.............\............\.....\mexRidgeRegression.m,1235,2013-08-01
.............\............\.....\mexRidgeRegression.mexw64,117248,2015-03-27
.............\............\.....\mexSimpleGroupTree.m,585,2013-06-24
.............\............\.....\mexSimpleGroupTree.mexw64,34816,2015-03-27
.............\............\.....\mexSOMP.m,2035,2012-03-15
.............\............\.....\mexSOMP.mexw64,118784,2015-03-27
.............\............\.....\mexSort.m,217,2012-03-15
.............\............\.....\mexSort.mexw64,22016,2015-03-27
.............\............\.....\mexSparseProject.m,2097,2012-03-22
.............\............\.....\mexSparseProject.mexw64,80384,2015-03-27
.............\............\.....\mexStochasticProx.m,2997,2013-12-04
.............\............\.....\mexStochasticProx.mexw64,531456,2015-03-27
.............\............\.....\mexStructTrainDL.m,5298,2013-06-24
.............\............\.....\mexStructTrainDL.mexw64,557056,2015-03-27
.............\............\.....\mexTrainDL.m,5619,2012-05-20
.............\............\.....\mexTrainDL.mexw64,221184,2015-03-27
.............\............\.....\mexTrainDL_Memory.m,4568,2012-05-15
.............\............\.....\mexTrainDL_Memory.mexw64,132608,2015-03-27

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  • ditonglvbo
    本文件是有关低通滤波器的程序，主要介绍了高斯低通滤波器。(This document is related to the low-pass filter procedure, introduces the Gaussian low-pass filter.)
    2014-03-14 19:52:51下载
    积分：1
  • sc_minutia
    指纹识别算法，开源，十分有用，是matlab语言编写的，直接可以用再做修改(about matching，very useful )
    2021-03-18 14:49:19下载
    积分：1
  • Smooth
    振动信号预处理。去噪、去趋势项等。滑动平均法消除趋势项。(Vibration signal preprocessing. De-noising, the trend term.)
    2013-05-14 09:25:38下载
    积分：1
  • MATLAB
    常规的中值滤波器，在噪声的密度不是很大的情况下效果不错。但是当概率出现的概率较高时，常规的中值滤波处理后，仍然具有噪声点，并丢失了细节和边缘，效果不是很好。 自适应中值滤波器可以尽可能的保护图像中细节信息，避免图像边缘的细化或者粗化。(The conventional median filter works well when the noise density is not very large. However, when the probability of probability is high, the conventional median filter still has noise points, and the details and edges are missing. The result is not very good. The adaptive median filter can protect details in the image as far as possible and avoid thinning or coarsening of the image edges.)
    2018-05-28 11:29:19下载
    积分：1
  • delineator
    对脉搏波的波峰波谷以及重搏波拐点的检测，挺好用的。。(On the pulse wave dicrotic wave peaks and valleys as well as the inflection point detection, very good use. .)
    2021-04-26 17:18:45下载
    积分：1
  • motion
    运动检测方法的实现， 这是最原始的方法实现，根据不同的应用可以对其进行相应的改进(Motion detection method realize that this is the most primitive method, according to different applications can be improved accordingly)
    2008-07-03 09:29:19下载
    积分：1
  • halcon-添加畸变及畸变矫正
    用halcon给实际采集的图像进行畸变矫正，然后可以再人为添加一定程度的畸变，以便于定量研究，可运行已调试，可作为学习参考(Halcon is used to correct the distortion of the image collected, and then the human can add some degree of distortion to facilitate quantitative research. It can be run and debugged, and can be used as a reference for study)
    2017-11-01 14:42:02下载
    积分：1
  • power-spectrum
    可同时实现多幅图片的傅里叶能量谱统计与分析！得到相应通道能量的信息！(Multiple images to achieve the power spectrum of Statistics and analysis!)
    2011-06-03 21:46:48下载
    积分：1
  • largestRectangleArea
    求一个图像的最大内接矩形面积。 步骤： 1.相机标定。首先根据物像关系式求出其中的参数。注意参数求出后要进行参数校验。 2.从背景中分离出目标 3.边缘检测 4.目标形状参数计算。(For an image of the largest inscribed rectangle area. Steps: 1. Camera calibration. First of all object-image relationship in accordance with the parameters obtained. Attention to the parameters obtained after parameter calibration. 2. From the context of isolated target 3. Edge detection 4. Target shape parameters.)
    2009-05-19 21:30:43下载
    积分：1
  • hunhegaosi
    混合高斯前景提取。数学建模时编的，测试视频就在包内，可以作为学习交流用，环境2014a的matlab，后有添加形态处理都在注释里。一起学习。有matlab编的vibe程序欢迎交流(Hybrid Gauss foreground extraction. Mathematical modeling of the series, the test video is in the package, can be used as a learning exchange, the environment 2014a MATLAB)
    2021-01-01 16:28:57下载
    积分：1
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