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24BMP256ColorGray
本代码实现的功能：24位位图（BMP）的灰度化。具体实现过程：打开图像文件,找到数据区(每3个字节代表一个象素的R,G,B值),循环扫描,根据RGB的权重,计算出灰度值. 如果要得到256色灰度图,则要新建一个调色板,修改信息头和文件头.(Realize the function of the code: 24-bit bitmap (BMP) of the gray. Concrete realization of the process: Open the image file, locate the data area (3 bytes per pixel on behalf of a R, G, B values), cyclic scan, according to the weight of RGB, gray value is calculated. If you want to get 256 colors grayscale, would create a new palette, modify the header and file header information.)
- 2020-07-01 01:20:02下载
- 积分：1
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何凯明图像去雾算法matlab程序与思路解读
说明： 何凯明图像去雾的算法MATLAB实现 以及改进(He kaiming image defogging algorithm MATLAB implementation and improvement)
- 2020-11-21 16:59:35下载
- 积分：1
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PG_BOW_DEMO
图像的特征用到了Dense Sift，通过Bag of Words词袋模型进行描述，当然一般来说是用训练集的来构建词典，因为我们还没有测试集呢。虽然测试集是你拿来测试的，但是实际应用中谁知道测试的图片是啥，所以构建BoW词典我这里也只用训练集。
其实BoW的思想很简单，虽然很多人也问过我，但是只要理解了如何构建词典以及如何将图像映射到词典维上去就行了，面试中也经常问到我这个问题，不知道你们都怎么用生动形象的语言来描述这个问题？
用BoW描述完图像之后，指的是将训练集以及测试集的图像都用BoW模型描述了，就可以用SVM训练分类模型进行分类了。
在这里除了用SVM的RBF核，还自己定义了一种核： histogram intersection kernel，直方图正交核。因为很多论文说这个核好，并且实验结果很显然。能从理论上证明一下么？通过自定义核也可以了解怎么使用自定义核来用SVM进行分类。(Image features used in a Dense Sift, by the Bag of Words bag model to describe the word, of course, the training set is generally used to build the dictionary, because we do not test set. Although the test set is used as the test you, but who knows the practical application of the test image is valid, so I am here to build BoW dictionary only the training set.
In fact, BoW idea is very simple, although many people have asked me, but as long as you understand how to build a dictionary and how to image map to the dictionary D up on the line, and interviews are often asked me this question, do not know you all how to use vivid language to describe this problem?
After complete description of the image with BoW, refers to the training set and test set of images are described with the BoW model, the training of SVM classification model can be classified.
Apart from having to use the RBF kernel SVM, but also their own definition of a nuclear: histogram intersection kernel, histogram )
- 2011-11-01 17:01:09下载
- 积分：1
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3
说明： 基于小波变换的水下图像目标检测论文加matlab实现代码(Wavelet-based underwater image target detection papers plus matlab code)
- 2013-09-12 22:16:31下载
- 积分：1
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Image_Restoration
此程序代码实现超分辨率图像的重建、复原 联合开发网 - pudn.com
- 2010-05-19 17:01:00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
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GEI
求质心到图像轮廓边缘的距离，并将其用figure表示出来(The distance from the center of mass to the edge of the image contour)
- 2021-03-22 10:59:17下载
- 积分：1
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jiami
生成混沌随机序列并实现对彩色图像的加密，(Encryption of color image)
- 2019-03-04 10:42:48下载
- 积分：1
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HUinvmoments
说明： HU的七个不变矩，每个文件是一个子程序，对应冈萨雷斯的数字图像处理教程的(HU)
- 2008-10-02 11:25:58下载
- 积分：1
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SAD
C++实现的SAD立体匹配算法，速度快，效果不错(SAD stereo matching method,it runs well.)
- 2021-01-19 16:38:42下载
- 积分：1
