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四参数随机生长法生成多孔介质代码
利用四参数随机生成法生成三维多孔介质，以研究黏土、页岩等的微观流动机制(Using QSGS to construct 3D porous media)
- 2021-03-29 17:29:10下载
- 积分：1
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whole_search_and_three-step_search
用matlab实现了图像通信中的全搜索算法与三步搜索算法这两种运动估值算法，给出了运动矢量图，对两种方法的计算复杂度和搜索性能进行了客观的比较。(Matlab image communication achieved by the full search algorithm in the three-step search algorithm with the two motion estimation algorithms, given the movement vector, the computational complexity of both methods and the search performance of objective comparison.)
- 2010-11-24 20:24:23下载
- 积分：1
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Image_Denoising_using_Fourth_Order_PDE
基于四阶偏微分方程的图像去噪算法，能够有效去除阶梯效应，自己编的程序(image denoising using fourth-order PDEs)
- 2009-04-03 11:46:23下载
- 积分：1
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石川公式MATLAB
说明： 利用石川啮合公式编写的程序，适用范围较广，好用，推荐(The program compiled by Ishikawa meshing formula is easy to use and recommended)
- 2020-11-09 16:29:46下载
- 积分：1
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fingerprint-OF-estimation
一种像素级指纹方向场估计算法以及对应的像素级奇异点检测算法。(A pixel-level orentation field estimation algorithm and the corresponding singular point detection method.)
- 2013-12-30 19:26:56下载
- 积分：1
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load_FRGC_abs_Z
三维人脸数据库FRGC V1. 0,2.0包括图像的深度数据和纹理，格式分别保存为：abs和ppm
读取abs数据中的深度z轴数据，保存为480*640的矩阵，进而进行数据处理研究。并且贴ppm纹理，便于观察。
(Three-dimensional face database FRGC V1. 0,2.0 depth data including images and textures, formats were saved as: abs abs data and ppm reads depth z-axis data, save it as a 480* 640 matrix, and then studied for data processing . And paste ppm texture, easy to observe.)
- 2021-04-12 13:48:57下载
- 积分：1
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meanshiftcode
视频目标跟踪算法,用meanshift方法对目标进行跟踪(meanshift algorithm tracking)
- 2010-06-09 19:56:43下载
- 积分：1
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Brief
说明： python实现的运用brief算法提取特征点的图像拼接(The implementation of Python using brief algorithm to extract feature points of image mosaic)
- 2020-04-25 18:33:43下载
- 积分：1
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matlab-white-noise--
用MATLAB产生高斯白噪声，并画出其时域波形、自相关函数和功率谱。(MATLAB white noise)
- 2011-12-16 15:52:15下载
- 积分：1
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SparseLab200-Core
基于多帧图像插值（Interpolation）技术的方法是SR恢复技术当中最直观
的方法。这类方法首先估计各帧图像之间的相对运动信息，获得HR图像在非均
匀间距采样点上的象素值，接着通过非均匀插值得到HR栅格上的象素值，最后
采用图像恢复技术来去除模糊和降低噪声（运动估计!非均匀插值!去模糊和
噪声）。(In this paper, we propose a novel method for solv-
ing single-image super-resolution problems. Given a
low-resolution image as input, we recover its high-
resolution counterpart using a set of training exam-
ples. While this formulation resembles other learning-
based methods for super-resolution, our method has
been inspired by recent manifold learning methods, par-
ticularly locally linear embedding (LLE). Speci?cally,
small image patches in the low- and high-resolution
images form manifolds with similar local geometry in
two distinct feature spaces. As in LLE, local geometry
is characterized by how a feature vector correspond-
ing to a patch can be reconstructed by its neighbors
in the feature space. Besides using the training image
pairs to estimate the high-resolution embedding, we
also enforce local compatibility and smoothness con-
straints between patches in the target high-resolution
image through overlapping. Experiments show that our
method is very ?exible )
- 2010-11-07 11:15:03下载
- 积分：1
