搜索资源列表
codes_smc
- 基于支撑向量机的的图像质量评价方法，结合机器学习和图像特征提取-The file feature_smc1.m is for feature extraction. It takes the reference and distorted images as input and gives the 256 dimensional feature vector as the output. models_smc_revised.mat contains the 4 models deve
tu-xiang-te-zheng
- MATLAB图像特征提取实战等各种代码。经测试能正常运行。-MATLAB image feature extraction combat other codes. Been tested to run correctly.
Image-Restoration-by-total-variation
- 基于全变分（TV）的多光谱遥感图像恢复。当多光谱图像中一个通道模糊时，利用其它通道的图像特征辅助进行去模糊或反卷积，效果不错-This is a new image restoration or deconvolution method, which uses one of clear band image to constraint Total Variation de-blurring of degraded band image in multispectral image. It tes
surfcheck
- 用surf算法完成了图像特征点的检测盒特征点的匹配-Completed with surf algorithm cartridge of the image feature points matching feature points
OpenCV_-image-feature-extraction
- OpenCV_局部图像特征的提取与匹配_源代码-OpenCV_ local image feature extraction and matching source code _
MyOpenCVConsole
- 常用的opencv图像特征提取算法。包括直方图、边缘检测、角点检测、直线提取、圆形提取等。并包括不太成熟的BP神经网络识别纯底色数字。-Commonly used opencv image feature extraction algorithm. Including histograms, edge detection, corner detection, line extraction, circular extraction. And includes less mature pure b
contourlet_toolbox
- 现在小波的发展越来越快，在小波的基础上又出现了超小波，轮廓波也是一种很重要的超小波，对于提取图像特征有很大的帮助-Now increasingly rapid development of wavelet, wavelet has emerged on the basis of super-wavelet contour wave is also a very important super wavelets for image feature extraction is very helpfu
CurveLab-1.0
- 在小波对图像特征提取的基础上，现在又出现了一种超小波，曲波就可以帮组大家提取轮廓边缘等特征-In wavelet based on image feature extraction, and now there is a super-wavelet, Qu Bo can help set you extract edge features such as contour
siftDemoV4
- SIFT发明人LOWE的SIFT特征提取程序代码及执行文件，用于图像特征点识别和图像拼接等。-LOWE inventor SIFT SIFT feature extraction program code and executable file for image feature point recognition and image stitching.
TestSIFTVC6
- 用opencv实现的sift的图像特征提取与匹配，有结果显示-Sift based on opencv image feature extraction and matching, according to the results
sift
- 一种常用于图像特征描述的一种描述子，全称尺度不变特征变换-Scale-invariant feature transform (or SIFT) is an algorithm in computer vision to detect and describe local features in images. The algorithm was published by David Lowe in 1999.[1]
forstner
- 利用常见的forster算子实现图像特征点提取，提取前用低通滤波去噪-Using common forster operator for image feature extraction, extraction with a low-pass filter denoising ago
opencv---sift
- 基于opencv的sift图像拼接算法，是特征匹配的一种，具有旋转、平移、遮蔽以及仿射不变形，广泛应用于图像拼接及图像特征匹配中-Based on the opencv sift image stitching algorithm, is a feature matching, rotation, translation, masking and affine deformation, is widely used in image stitching and image feature mat
edgehist
- 图像特征提取算法，可供学生学习参考，用的是c++语言写的。-Image feature extraction algorithm, for students to learn reference, using c++ Language writing.
lear_gist-1.2
- 图像特征提取 gist feature,限mac/linux平台-Image feature extraction gist feature, limit mac/linux platform
ICAforImage
- ica对图像的特征提取与还原。。很好用，自己在使用中，推荐下载
CCA
- 典型相关性分析，对图像特征及其文本特征进行融合，抽取主要特征并存储输出，是很好的跨媒体领域处理算法-Canonical correlation analysis, features and text features for image fusion, extract and store the output of the main features is a good cross-media field processing algorithms
SAR
- sar图像特征提取 合成孔径雷达图像特征 -sar image feature extraction synthetic aperture radar image features sar image feature extraction feature synthetic aperture radar image
image-analysis
- 包含图像特征分析与图像形态学，针对bitmap-an image analysis and image morphological features for bitmap
multiobject_context
- 多类图像特征结合上下文信息进行目标识别（分类、分割）-Many types of image features combined with context information for target identification (classification, segmentation)