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43659358Matlab-GUI--for-Image-Segmentation--
基于MATLAB GUI的图像处理界面，包括基本的图像处理功能(Graphical interface construction based on image processing)
- 2019-04-23 17:27:02下载
- 积分：1
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unwrapfile
说明： 用于相位解缠，提供好的解缠方法和解缠效果，能够更好的得到真实值(For phase unwrapping, unwrapping methods provide good wrapped around the effect of reconciliation that can better be the true value)
- 2008-11-04 14:14:36下载
- 积分：1
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RECOVER
比较反滤波和维纳滤波对一幅图像复原的效果。从两方面出发，一是对运动模糊和均值模糊复原的能力，二是抗噪能力，各种情况分别都进行了对比(Comparison of inverse filtering and Wiener filtering on an image restoration results. Proceed in two ways, first on the motion blur and the mean fuzzy recovery capability and noise immunity, all cases are compared separately)
- 2010-06-02 03:44:47下载
- 积分：1
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fouriermellin
本代码是完成傅里叶梅林变换对图像的旋转剪切。没有嵌入水印。(The code is complete Fourier Mellin transform of the image rotation shear. No embedded watermark.)
- 2010-05-17 16:29:41下载
- 积分：1
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pingjiehefengbu
图像的自动拼接和缝补，采用sift算法作为匹配，是学习全景图像拼接的基础，大家可以下载下来看看(Automatic image stitching and sewing, using sift algorithm as a match, is the basis for learning panoramic image mosaic, you can download to see)
- 2011-10-21 18:49:58下载
- 积分：1
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ImgZoom
OPENCV做图像变形的经典代码啊，适合比较初级的同学看看(OPENCV do image warping the classic code ah, suitable for elementary students to see more)
- 2009-12-02 20:06:13下载
- 积分：1
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SITFbasedmatch
包括基于SIFTGPU的sift特征提取，sift匹配，基于ransac误匹配点剔除等(SIFTGPU based sift feature extraction, sift matching, mismatching points based ransac removed, etc.)
- 2021-04-09 22:38:59下载
- 积分：1
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1231
火灾探测中火焰图像分割方法研究,比较实用。(Fire detection fire image segmentation, more practical.)
- 2010-12-07 13:34:27下载
- 积分：1
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Face_PCA
在人脸数据库中应用PCA，以及重建误差分析(Applying PCA in human face dataset and doing analysis on reconstruction differences )
- 2020-07-15 10:18:51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
