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PyShearlets

于 2019-10-08 发布
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下载积分: 1 下载次数: 1
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代码说明：

说明：  剪切波代码实现 有Matlab和python两个版本 都是可以运行和跑通的(The implementation of shear wave code has two versions: MATLAB and python, which can run and run.)

文件列表：

PyShearlets\.git\config, 305 , 2019-08-31
PyShearlets\.git\description, 73 , 2019-08-31
PyShearlets\.git\HEAD, 23 , 2019-08-31
PyShearlets\.git\hooks\applypatch-msg.sample, 478 , 2019-08-31
PyShearlets\.git\hooks\commit-msg.sample, 896 , 2019-08-31
PyShearlets\.git\hooks\fsmonitor-watchman.sample, 3327 , 2019-08-31
PyShearlets\.git\hooks\post-update.sample, 189 , 2019-08-31
PyShearlets\.git\hooks\pre-applypatch.sample, 424 , 2019-08-31
PyShearlets\.git\hooks\pre-commit.sample, 1638 , 2019-08-31
PyShearlets\.git\hooks\pre-push.sample, 1348 , 2019-08-31
PyShearlets\.git\hooks\pre-rebase.sample, 4898 , 2019-08-31
PyShearlets\.git\hooks\pre-receive.sample, 544 , 2019-08-31
PyShearlets\.git\hooks\prepare-commit-msg.sample, 1492 , 2019-08-31
PyShearlets\.git\hooks\update.sample, 3610 , 2019-08-31
PyShearlets\.git\index, 3102 , 2019-08-31
PyShearlets\.git\info\exclude, 240 , 2019-08-31
PyShearlets\.git\logs\HEAD, 195 , 2019-08-31
PyShearlets\.git\logs\refs\heads\master, 195 , 2019-08-31
PyShearlets\.git\logs\refs\remotes\origin\HEAD, 195 , 2019-08-31
PyShearlets\.git\objects\pack\pack-929d165ccfb1b536e243716f037f2be18e3c468e.idx, 4740 , 2019-08-31
PyShearlets\.git\objects\pack\pack-929d165ccfb1b536e243716f037f2be18e3c468e.pack, 90137 , 2019-08-31
PyShearlets\.git\packed-refs, 465 , 2019-08-31
PyShearlets\.git\refs\heads\master, 41 , 2019-08-31
PyShearlets\.git\refs\remotes\origin\HEAD, 32 , 2019-08-31
PyShearlets\.gitattributes, 31 , 2019-08-31
PyShearlets\.gitignore, 628 , 2019-08-31
PyShearlets\.travis.yml, 836 , 2019-08-31
PyShearlets\COPYING, 35821 , 2019-08-31
PyShearlets\doc\conf.py, 9815 , 2019-08-31
PyShearlets\doc\index.rst, 1798 , 2019-08-31
PyShearlets\doc\Makefile, 6982 , 2019-08-31
PyShearlets\doc\reference\.gitignore, 7 , 2019-08-31
PyShearlets\doc\sphinxext\docscrape.py, 18135 , 2019-08-31
PyShearlets\doc\sphinxext\docscrape_sphinx.py, 7986 , 2019-08-31
PyShearlets\doc\sphinxext\github.py, 5534 , 2019-08-31
PyShearlets\doc\sphinxext\math_dollar.py, 2106 , 2019-08-31
PyShearlets\doc\sphinxext\numpydoc.py, 6826 , 2019-08-31
PyShearlets\doc\tools\apigen.py, 18499 , 2019-08-31
PyShearlets\doc\tools\buildmodref.py, 2143 , 2019-08-31
PyShearlets\doc\tools\LICENSE.txt, 253 , 2019-08-31
PyShearlets\examples\example.py, 3352 , 2019-08-31
PyShearlets\FFST\meyerShearlet.py, 5802 , 2019-08-31
PyShearlets\FFST\shearletScaleShear.py, 5438 , 2019-08-31
PyShearlets\FFST\tests\test_ffst.py, 3536 , 2019-08-31
PyShearlets\FFST\tests\__init__.py, 0 , 2019-08-31
PyShearlets\FFST\_fft.py, 4662 , 2019-08-31
PyShearlets\FFST\_inverseShearletTransformSpect.py, 2317 , 2019-08-31
PyShearlets\FFST\_scalesShearsAndSpectra.py, 7759 , 2019-08-31
PyShearlets\FFST\_shearletTransformSpect.py, 3063 , 2019-08-31
PyShearlets\FFST\_version.py, 17223 , 2019-08-31
PyShearlets\FFST\__init__.py, 418 , 2019-08-31
PyShearlets\MANIFEST.in, 49 , 2019-08-31
PyShearlets\README.orig, 3120 , 2019-08-31
PyShearlets\README.rst, 840 , 2019-08-31
PyShearlets\setup.cfg, 158 , 2019-08-31
PyShearlets\setup.py, 503 , 2019-08-31
PyShearlets\versioneer.py, 67521 , 2019-08-31
PyShearlets\.git\logs\refs\remotes\origin, 0 , 2019-08-31
PyShearlets\.git\logs\refs\heads, 0 , 2019-08-31
PyShearlets\.git\logs\refs\remotes, 0 , 2019-08-31
PyShearlets\.git\refs\remotes\origin, 0 , 2019-08-31
PyShearlets\.git\logs\refs, 0 , 2019-08-31
PyShearlets\.git\objects\info, 0 , 2019-08-31
PyShearlets\.git\objects\pack, 0 , 2019-08-31
PyShearlets\.git\refs\heads, 0 , 2019-08-31
PyShearlets\.git\refs\remotes, 0 , 2019-08-31
PyShearlets\.git\refs\tags, 0 , 2019-08-31
PyShearlets\.git\hooks, 0 , 2019-08-31
PyShearlets\.git\info, 0 , 2019-08-31
PyShearlets\.git\logs, 0 , 2019-08-31
PyShearlets\.git\objects, 0 , 2019-08-31
PyShearlets\.git\refs, 0 , 2019-08-31
PyShearlets\doc\reference, 0 , 2019-08-31
PyShearlets\doc\sphinxext, 0 , 2019-08-31
PyShearlets\doc\tools, 0 , 2019-08-31
PyShearlets\FFST\tests, 0 , 2019-08-31
PyShearlets\.git, 0 , 2019-10-08
PyShearlets\doc, 0 , 2019-08-31
PyShearlets\examples, 0 , 2019-08-31
PyShearlets\FFST, 0 , 2019-08-31
PyShearlets, 0 , 2019-08-31

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    ASM是由Cootes和泰勒推出的多分辨率方法的一个例子。 基本思想： 在ASM模型训练，训练从手工绘制的图像轮廓。发现的ASM模型在训练使用主成分分析（PCA），使该模型自动识别数据的主要变化是，如果可能的轮廓/好的对象的轮廓。还包含了ASM模型的协方差矩阵描述行垂直纹理口岸时，在正确的位置。 (Description This is an example of the basic Active Shape Model (ASM) as introduced by Cootes and Taylor, with multi-resolution approach. Basic idea: The ASM model is trained from manually drawn contours in training images. The ASM model finds the main variations in the training data using Principal Component Analysis (PCA), which enables the model to automatically recognize if a contour is a possible/good object contour. Also the ASM models contains covariance matrices describing the texture of the lines perpendicular to the control points when in the correct positions. After creating the ASM model, an initial contour is deformed by finding the best texture match for the control points. This is an iterative process, in which the movement of the control points is limited by what the ASM model recognizes from the training data as a "normal" object contour. Literature: - Ginneken B. et al. "Active Shape Model Segmentation with Optimal Features", IEEE Transactions on Medical I)
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    当信噪比较大时，采用广义最小二乘法可能会出现多个局部收敛点，解决这个问题的方法可用多级最小二乘法，一般来说多级最小二乘法包含三级辨识过程。利用输入输出数据，通过多级最小二乘法，可分别求的辅助模型，过程模型和噪声模型的参数估计值。在高噪声的情况下，多级最小二乘法明显优于广义最小二乘法，其收敛点唯一。(When the signal noise ratio (SNR), and by use of the generalized least squares method may appear more local convergence point, the way of solving this problem can be used multistage least squares method, and generally multistage least squares method includes three identification process. Using input/output data, through the multistage least squares, respectively for the auxiliary model, process model and noise model parameter estimation. In the high noise, multistage least squares method is obviously superior to the generalized least squares method, and its convergence point only.)
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