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tiaxian
自适应波束形成的三个准则：MMSELCMVMSINR(Three criteria for adaptive beamforming: MMSELCMVMSINR)
- 2021-03-13 16:49:24下载
- 积分：1
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shotdetection(matlab)
视频分割的matlab 程序,是用matlab开发的一个视频分割程序(Matlab video segmentation procedures are developed using matlab a video segmentation process)
- 2009-02-17 14:20:22下载
- 积分：1
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opencvorb
利用Orb算法实现图像特征点的提取，并且通过前后两帧之间的特征点进行特征匹配，为视频稳像、图像融合以及图像识别提供前提条件。(Detecting feature points using Orb algorithm, then matching the points with the detected points frames.That method provide one new way to video stablization ,image fusion and image recognition etc. )
- 2015-08-22 11:29:26下载
- 积分：1
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图像分割
说明： 图像自适应阈值分割，基于直方图的图像阈值分割(Image adaptive threshold segmentation)
- 2019-01-18 11:37:17下载
- 积分：1
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xbnl
小波包分解，求能量程序，，对小波包的了解掌握都很有用，希望对读者游泳(the wavelet packet decomposition and energy distribution )
- 2016-08-01 20:18:07下载
- 积分：1
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bridge
压缩包里面为2个程序，一个是悬链线模拟索的程序，一个是抛物线法模拟的索的程序(Compressed inside of two programs, one cable catenary simulation program, a parabolic law analog cable programs)
- 2021-06-08 15:30:07下载
- 积分：1
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RegionGrow921
基于区域增长的图像分割算法，非常经典，用MATLAB编写，已测试可用，对新手有帮助(Based on region growing image segmentation algorithm, very classic, with MATLAB writing, have been tested is available on the novice help)
- 2009-09-27 14:56:34下载
- 积分：1
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计算图像信息熵
计算一幅图像的熵，matlab编程文件，任意读取一幅图像，计算信息熵(Calculate the entropy of an image)
- 2017-11-26 14:22:55下载
- 积分：1
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PCA
主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)
- 2021-01-28 21:48:40下载
- 积分：1
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xiaobo
数字图像处理 小波处理 ，去噪音，比基于傅里叶变换的去噪方法好。
含噪信号经过预处理，然后利用小波变换把信号分解到各尺度中，在每一尺度下把属于噪声的小波系数去掉，保留并增强属于信号的小波系数，最后再经过小波逆变换恢复检测信号。(The noisy signal is pre-processed, then the signal is decomposed into different scales by wavelet transform. The wavelet coefficients belonging to noise are removed at each scale, and the wavelet coefficients belonging to the signal are retained and enhanced. Finally, the detected signal is restored by inverse wavelet transform. It is better than the denoising method based on Fourier transform.)
- 2019-06-04 10:40:35下载
- 积分：1
