搜索资源列表
MATLAB_Image_subpixel_Mutual_i
- MATLAB实现基于互相关的亚像素级图像配准源代码,MATLAB_Image_subpixel_Mutual_info,MATLAB-based cross-correlation of sub-pixel image registration source code, MATLAB_Image_subpixel_Mutual_info
normxcorr2_mex_ALL
- 归一化互相关高速计算模块OpenCV工程,Daniel Eaton已将其生成Matlat Mex文件,比Matlab内建的normxcorr2()效率要高-Normalized cross-correlation of high-speed calculation module, Daniel Eaton have been wrapped the C++ code from OpenCV project and making it available as a MATLAB MEX-file,
15
- matlab 图像处理 显示两幅子图像的归一化互相关-matlab image processing show that two sub-image of normalized cross-correlation
crosscorrelation
- 基于最大互相关的图像匹配，是本人的毕业设计，希望对大家有帮助。-The largest cross-correlation-based image matching, is my graduation project, I hope there is help for everyone.
videopatternmatching
- 本程序展示了二维归一化互相关用于 模式匹配和目标跟踪。该程序提示用户选择感兴趣的（ROI）的区域和对同类目标进行跟踪的数目。归一化交叉相关图表明，当值已超过设定的阈值时目标就已经确定。-This demo illustrates the use of 2-D normalized cross-correlation for pattern matching and target tracking. The demo prompts the user to select
code
- 依据自相关运算和互相关运算的原理，对一信号进行自相关操作-Based on autocorrelation and cross correlation by using the principle of a signal from the correlation operation
ex_15_1
- 图像配准：选择图像需要配准的子区域，计算归一化互相关，通过它来确定图像配准的区域，显示配准后的图像。-Image registration: Select the image sub-region need registration, computing normalized cross-correlation, by which to determine the image registration area to show the image after registration.
xianguan
- 首先给图片添加噪声，然后实现图片的自相关和互相关！最后显示出来！-First, adding noise to the picture, and then realize the image autocorrelation and cross correlation! Finally displayed!
hxcorr1
- 实现图像的圆周互相关，对初学者很有用，可以实现图像的相关检测-The circular cross-correlation of image, is useful for beginners, the image correlation detection can be achieved
Mypic
- 采用模板匹配方法进行图像匹配，其中误差平方和测度经过归一化互相关处理。-Using template matching method for image matching, in which the error sum of squares measure through normalized cross correlation processing.
Frances-tracking-algorithm
- 一个法国新三维跟踪算法，使用了信息互相关，实现增强现实等非常稳定-France s new three-dimensional tracking algorithm
test_10_21
- 图像拼接源码 ，合称360度全景图 采用归一化互相关-Source image stitching, collectively known as 360-degree panorama using normalized cross-correlation
huxiangguan
- 两副图片的频域互相关,没啥好说的,图象处理书上有算法,懂就懂,不懂就算,-Two images in the frequency domain cross-correlation, nothing to say, the book on image processing algorithms, to understand to understand, do not know even if,
target
- 通过计算最大互相关（Cross Correlation），在给定的图像中检测目标图像，并在图像显示窗口中高亮该区域-By calculating the maximum cross-correlation (Cross, The Correlation), detection of the target image in a given image, and highlight the region in the image display window
xiangguan
- 基于互相关matlAB图像配准代码，压缩文件包括源文件，GUI设计文件。程序能自动配准图像，能手动选择要配准的图像-Based on cross-correlation matlAB image registration code, source files, including compressed files, GUI design files. Automatic image registration procedures, registration can manually select
image-mosaic.doc
- 图像拼接(image mosaic)技术是将一组相互间重叠部分的图像序列进行空间匹配对准,经重采样合成后形成一幅包含各图像序列信息的宽视角场景的、完整的、高清晰的新图像的技术。图像拼接在摄影测量学、计算机视觉、遥感图像处理、医学图像分析、计算机图形学等领域有着广泛的应用价值。 一般来说,图像拼接的过程由图像获取,图像配准,图像合成三步骤组成,其中图像配准是整个图像拼接的基础。本文研究了两种图像配准算法:基于特征和基于变换域的图像配准算法。 在基于特征的配准算法的基础上,提出一种稳健的基于特征点的
Image20160331Quality
- 测试以下图像信息 1。结构内容（SC） 2。均方误差（MSE） 3。峰值信噪比（PSNR值） 4。归一化互相关（NCC） 5。平均差（AD） 6。最大的差异（MD） 7。归一化绝对误差（NAE）-Image/Picture Quality Measures In this application, different image quality measures are calculated for a distorted image with refere
交叉相关法实现图像精准匹配
- Matlab基于互相关法原理实现图像的快速精确匹配(Using matlab realizes fast and accurate image matching based on cross-correlation principle)
NCC
- 将归一化互相关应用到图像配准上，使用互相关来判断两幅图像的相似性，相似度越大，说明配准结果越是精确。(The normalized cross-correlation is applied to image registration, and the similarity of two images is judged by cross-correlation. The greater the similarity, the more accurate the registration resu
ky058
- 通过反复训练模板能有较高的识别率，ICA（主分量分析）算法和程序，包括广义互相关函数GCC时延估计。( Through repeated training TegCJHclate have higher recognition rate, ICA (Principal Component Analysis) algorithm and procedures, Including the generalized cross-correlation function GCC time delay e