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Houghtranslate
这个是图像处理中的hough变换的C++源代码，工需要的同学参考学习。(This is the image processing hough transform C++ source code, engineering students need to learn.)
- 2013-09-07 00:28:11下载
- 积分：1
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picture-calibration
这是图像校正程序，matlab运行环境，是我自己编的，可能没那么完美，还要有改进的地方(This is the picture calibration procedures)
- 2012-03-20 11:15:52下载
- 积分：1
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niqe_release
用于无参考帧图像质量评价的MATLAB程序，运行程序为example，输出图像的客观分值。(This is the matlab code of no-reference image qualituy assessment in space domain, th result ofthe program is the object acore of the image.)
- 2021-01-05 15:48:54下载
- 积分：1
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ImageRestore2
说明： 基于fft的数字图像处理MATLAB实现(Fft based on MATLAB for digital image processing to achieve)
- 2009-08-03 15:33:46下载
- 积分：1
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Harris2
Harris角点检测，关于角点的应用在图像处理上比较广泛，如图像匹配(FPM特征点匹配)、相机标定等。网上也有很多博客对Harris角点检测原理进行描述，但基本上只是描述了算法流程，而其中相关细节并未作出解释，这里我想对有些地方做出补充说明，正所谓知其然知其所以然，如有不对，还望指正。(Harris corner detection)
- 2019-06-13 22:02:03下载
- 积分：1
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zhenjiancha55
帧间差法实现视频对象的分割，进行运动目标的检测小程序。(The frame difference method of video object segmentation, moving target detection procedures.)
- 2020-07-02 08:20:01下载
- 积分：1
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histeq
主成分分析算法（PCA），可用于降维，也可用于处理图像相关性问题，提取主成分，分析图像细节信息和主要成分，用于图像压缩也可以(Principal component analysis algorithm (PCA), can be used for dimensionality reduction, can also be used to process images related issues, extracted principal component analysis and main component of image detail information, to be used for image compression)
- 2015-04-15 21:40:51下载
- 积分：1
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CIE_chromaticity_diagram
CIE色度图, CIE 1931 RGB, CIE 1931 XYZ, CIE 1931 xyY(CIE chromaticity diagram, CIE 1931 RGB, CIE 1931 XYZ, CIE 1931 xyY)
- 2020-10-28 20:39:58下载
- 积分：1
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MCtest
一种基于MC算法的医学图像三维重建，或许有用(MC algorithm based on three-dimensional reconstruction of medical images, perhaps useful)
- 2009-01-24 12:59:49下载
- 积分：1
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demoBagSVM
一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章：Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。(A semi-supervised SVM is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image, and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictionsds)
- 2013-09-03 10:44:56下载
- 积分：1
