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Image-deblurring-
一份关于用正则化去除图像模糊的资料，内含代码以及说明，并附上了仿真结果图(A report on the Regularization blur removal image data containing codes and descriptions, along with the simulation results of FIG.)
- 2016-03-26 14:30:40下载
- 积分：1
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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！！附带有对应的文章做参考。(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 tested with different noise with different regularization parameters. It also compared with otherhods.)
- 2013-08-30 22:13:45下载
- 积分：1
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145
一个很好类子来说明类模板的使用，可以比较明了类模板的使用方法，最好进行单步调试(use of class template )
- 2013-08-30 17:17:58下载
- 积分：1
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mtf
可以用来计算MTF值，用matlab编写的，数据文件需要为Excel格式。(MTF can be used to calculate the value, using matlab prepared.)
- 2009-11-28 18:46:44下载
- 积分：1
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tuxiangyuchuli
图片的预处理 将图片读入之后 经过灰度处理 中值滤波（多次） sobel算子运算
二值化运算 最后做细化 处理 显示并保存 细化后的图象(Pretreatment of the picture after the picture to read through the gray scale median filter processing (multiple) sobel operator Binary operator to do the final thinning operation display and save the image after thinning)
- 2011-06-05 20:19:11下载
- 积分：1
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图像拼接
说明： 利用python和opencv拼接两张图片(Splicing two pictures using Python and opencv)
- 2020-06-17 07:40:01下载
- 积分：1
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faceDetection_HOG
说明： 利用HOG算子实现电脑读取图像并进行面部识别与检测(Using hog operator to realize computer reading image and face recognition and detection)
- 2020-10-11 11:09:27下载
- 积分：1
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watershed_segmentation
基于分水岭的迭代式分割算法演示，基于matlab7.6，可有效并且准确的分割目标图像(A demo for image segmentation using iterative watersheding plus ridge detection)
- 2009-12-23 09:29:56下载
- 积分：1
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quyufenlie
选择一副灰度图像，用区域分裂合并法对其进行分割(Choose a grayscale image, with its regional divisions split merge method)
- 2011-06-25 22:08:11下载
- 积分：1
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InversePerspectiveMapping
对输入的图像帧感兴趣区域进行逆透视投影变换，得到俯视图。(The input of the image frame of interest in the area of the inverse perspective projection transform, get a top view.
InversePerspectiveMapping)
- 2016-12-04 21:31:56下载
- 积分：1
