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chapter02
matlab6.5图形图像处理源程序 部分内容 第二章压缩包 (matlab6.5 )
- 2013-10-27 13:02:04下载
- 积分：1
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Latent SVM算法实现行人检测opencv
Latent SVM算法实现行人检测opencv(Latent SVM Pedestrian Detection Based on Algorithms opencv)
- 2020-06-25 15:20:02下载
- 积分：1
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SNR
计算一副图像，或者加噪声后图像信噪比和峰值信噪比，代码非常简洁方便，效率很高。(Calculate the image SNR and PSNR)
- 2021-03-15 15:09:22下载
- 积分：1
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SARSimulation
合成孔径雷达（SAR）回波模拟半实物仿真平台的构建(Synthetic aperture radar (SAR) analog echo-loop Simulation Platform)
- 2009-07-07 22:23:20下载
- 积分：1
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SARclassify
SAR图像分类程序，基于灰度阈值的分类，无监督学习的分类简单。(SAR Image classification)
- 2011-06-30 01:49:17下载
- 积分：1
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HSV
实现RGB到HSV空间转换，之后提取H、S、V分量后获取图像的颜色直方图和累计颜色直方图。(Achieve RGB to HSV space conversion, after the extraction of H, S, V components to obtain the image of the color histogram and cumulative color histogram.)
- 2021-04-18 08:38:52下载
- 积分：1
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read_nc
本代码用于实现.nc文件的IDL代码打开，并且可以实现，根据经纬度找到相应的像元值(This code is used to implement. Nc file IDL code open, and can be implemented, according to the longitude and latitude as yuan values can be found)
- 2015-04-05 20:43:54下载
- 积分：1
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guituxingzhuanghuan
gui图形界面导入多张图片并转换为偏振图(gui graphical interface to import multiple images and convert polarizing figure)
- 2020-06-29 01:20:01下载
- 积分：1
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retinalsegmentation
说明： 文献 基于灰度-梯度共生矩阵的视网膜血管分割方法(Literature based on the gray- the gradient co-occurrence matrix of the retinal blood vessel segmentation method)
- 2009-07-28 06:35:00下载
- 积分：1
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GMM高斯混合模型进行背景建模（Matlab）
转：https://blog.csdn.net/jinshengtao/article/details/26278725
混合高斯背景建模是基于像素样本统计信息的背景表示方法，利用像素在较长时间内大量样本值的概率密度等统计信息(如模式数量、每个模式的均值和标准差)表示背景，然后使用统计差分(如3σ原则)进行目标像素判断，可以对复杂动态背景进行建模，计算量较大。
在混合高斯背景模型中，认为像素之间的颜色信息互不相关，对各像素点的处理都是相互独立的。对于视频图像中的每一个像素点，其值在序列图像中的变化可看作是不断产生像素值的随机过程，即用高斯分布来描述每个像素点的颜色呈现规律单模态(单峰)，多模态(多峰)(Gaussian mixture background modeling is a background representation method based on the statistical information of pixel samples. Statistical information such as the number of patterns, the mean and standard deviation of each pattern are used to represent the background. Statistical difference (such as 3_principle) is used to judge the target pixel. Complex dynamic background modeling has a large amount of computation.
In the Gaussian mixture background model, it is considered that the color information between pixels is uncorrelated and the processing of each pixel is independent of each other. For each pixel in a video image, the change of its value in a sequential image can be seen as a random process that produces pixel values continuously, i.e. Gaussian distribution is used to describe the regularity of color rendering of each pixel in single mode (single peak) and multi-mode (multi-peak).)
- 2020-11-01 09:49:54下载
- 积分：1
