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图像处理中的一些常用代码Image-processing-code(4)

于 2020-07-09 发布 文件大小:1KB
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  图像处理中的一些常用代码,包括:腐蚀操作 开启和闭合操作 形态学边界提取 形态学骨架提取 直接提取四个顶点坐标(Some of the commonly used image processing code, including: Opening and closing operation of corrosion morphology boundary extraction morphological skeleton extraction to extract four vertex coordinates)

文件列表:

Image processing code(4).m,3458,2015-08-27

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    2010-04-20 18:44:00下载
    积分:1
  • motiondetection
    完整的程序,提供测试视频帧。根据视频帧中图像的形状进行运动估计(integrity of the procedures for testing video frames. According to Video Frame Image Motion Estimation shape)
    2006-09-07 21:38:28下载
    积分:1
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    去除高斯噪声的有效码源,去噪能力强,使简单。(The effective removal of Gaussian noise source code, denoising capability, so that simple.)
    2008-04-01 17:55:27下载
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    Visual C++下的小波变换,小波分解与重构,加入噪声分析,显示分解和重构图形。(Wavelets for data encode and uncode, the figures would be shown.)
    2009-04-09 21:55:21下载
    积分:1
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    对SAR图像分割 用马尔科夫随机长进行的。可以任意输入类别数目(For SAR image segmentation using Markov old airport)
    2020-07-01 09:00:02下载
    积分:1
  • Speckle_reduction
    用于SAR图像的相干斑抑制,内有增强Lee滤波,增强Kuan滤波,增强GammaMap滤波算法,还有等效视数,边缘保持指数的求法(For speckle suppression of SAR images, there are enhanced Lee filtering, enhanced Kuan filtering, enhanced GammaMap filtering algorithm, and the calculation of ENL and EPI.)
    2019-03-30 17:23:15下载
    积分:1
  • surf2stl
    基于surf的图像复制篡改检测matlab实现(surf image detect matlab)
    2012-02-14 11:11:42下载
    积分:1
  • pcnn
    说明:  基于脉冲耦合神经网络的图像分割,脉冲耦合神经网络是近年研究的热点。(Based on Pulse Coupled Neural Network for Image Segmentation, pulse coupled neural network is the research hotspot in recent years.)
    2008-11-23 09:36:27下载
    积分:1
  • SumDifCombineview
    立体图像左右视点融合,将左右图像利用LogGabor融合成一幅图像。(Stereo image fusion, the left and right image are fused into an image using LogGabor.)
    2015-10-14 14:10:26下载
    积分:1
  • liantongyuzongmianjiyushuliang_DGlearn
    说明:  通过利用“Otsu”方法对图像进行全局阈值分割处理。然后,将灰度图转化成二值图,为获得大豆颗粒计数和大小做准备。调用函数获得图像连通图的数量,并测量标注矩阵中每个标注区域的属性,获得每个标注区域的长度。最后通过寻找每个区域的重心数,即可统计出大豆的个数(The Otsu method is used to segment the image. Then, the gray-scale image is transformed into a binary image to prepare for the soybean particle count and size. Call the function to get the number of connected graphs, measure the attributes of each annotation region in the annotation matrix, and get the length of each annotation region. Finally, the number of soybean can be calculated by finding the number of barycenters in each region)
    2019-11-14 22:33:51下载
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