文件名称:SURF-based-image-stitching
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2014-08-30
- 文件大小：
- 1.97mb
- 下载次数：
- 0次
- 提 供 者：
- 马*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。
采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。
-SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching.
This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching.
采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。
-SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching.
This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching.
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下载文件列表
基于SURF的图像拼接\example3.m
..................\findHomography.m
..................\main.fig
..................\main.m
..................\OpenSurf.m
..................\randIndex.m
..................\ransac1.m
..................\solveHomo.m
..................\SubFunctions\FastHessian_BuildDerivative.m
..................\............\FastHessian_buildResponseLayer.m
..................\............\FastHessian_buildResponseMap.m
..................\............\FastHessian_getIpoints.m
..................\............\FastHessian_getLaplacian.m
..................\............\FastHessian_getResponse.m
..................\............\FastHessian_interpolateExtremum.m
..................\............\FastHessian_isExtremum.m
..................\............\FastHessian_ResponseLayer.m
..................\............\IntegralImage_BoxIntegral.m
..................\............\IntegralImage_HaarX.m
..................\............\IntegralImage_HaarY.m
..................\............\IntegralImage_IntegralImage.m
..................\............\PaintSURF.m
..................\............\SurfDescriptor_DecribeInterestPoints.m
..................\............\SurfDescriptor_GetDescriptor.m
..................\............\SurfDescriptor_GetOrientation.m
..................\TestImages\1.jpg
..................\..........\2.jpg
..................\Untitled.m
..................\WarpFunctions\affine_warp.m
..................\图片\1(1).jpg
..................\....\1(2).jpg
..................\....\2(1).jpg
..................\....\2(1).png
..................\....\2(2).jpg
..................\....\2(2).png
..................\....\2.jpg
..................\....\3(1).jpg
..................\....\3(2).jpg
..................\....\3(2).png
..................\....\3.jpg
..................\SubFunctions
..................\TestImages
..................\WarpFunctions
..................\图片
基于SURF的图像拼接