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heavy-tailed-deconv
一般自然图像的梯度分布符合重尾分布，重尾分布也就是超拉普拉斯分布，根据这个特点进行图像复原。(The gradient of a natural image in line with heavy-tailed distribution, which is ultra-heavy-tailed distribution Laplace distribution, image restoration based on this feature.)
- 2021-03-13 10:39:24下载
- 积分：1
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background
实现帧差法求背景的matlab程序和示例图片(Frame-difference method to achieve the background image matlab procedures and sample)
- 2009-05-04 20:06:07下载
- 积分：1
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Kalman_Filter
卡尔曼滤波源代码
Some brief notes
----------------
kfdemo.m is a Matlab script file to run a demonstration of the
Bayesian Kalman filter. It loads file kfdemo.mat (saved as version 4
so that it will read in either v4 or v5 Matlab).
The other files are called by kf.m (the Kalman filter) or included
as they may be useful. Normalis.m normalises data to zero-mean,
unit variance along components. I always do this before any further
analysis.
Steve Roberts 7-2-98
(Kalman filter source code Some brief notes kfdemo.m is a Matlab script file to run a demonstration of theBayesian Kalman filter. It loads file kfdemo.mat (saved as version 4so that it will read in either v4 or v5 Matlab). The other files are called by kf.m (the Kalman filter) or includedas they may be useful. Normalis.m normalises data to zero-mean, unit variance along components. I always do this before any furtheranalysis.Steve Roberts 7-2-98)
- 2008-04-05 16:47:47下载
- 积分：1
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test
一个简短的计算图像信息熵的程序，对于初学IDL的开发者来说，有一定的借鉴作用(A brief image information entropy calculation procedure, IDL for beginner developers who have a certain reference)
- 2011-11-19 23:09:46下载
- 积分：1
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matlab.thresholding-master
在计算机视觉中，图像分割是将图像分成多个片段的过程。这使我们能够通过以比原始图像更简单的表示方式来更好地分析图像。一种用于分割图像的方法是阈值分割；也就是说，将强度值低于阈值的所有像素设置为背景值，而将高于阈值的其他像素设置为前景值。最简单的阈值处理形式是对所有像素使用全局阈值，而自适应阈值处理根据像素及其周围环境动态改变阈值。典型地，阈值处理从灰度图像开始，并输出二进制图像以清晰地描绘图像中的片段。在本实验中，我们开发了一种自适应阈值算法，并将其与更简单的算法进行了比较。 此外，我们还开发了逆运动学证明来将机械臂移动到给定的x，y，z坐标。这一证明涉及三种命名身份，并获得了对机械臂设计的更好理解。(Image threshold segmentation)
- 2019-04-14 15:41:02下载
- 积分：1
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Inpainting--on-Wavelet-
图像修复是图像处理的一个重要问题。这是一个困难的问题，同时填写在地区缺少图像信息的纹理和结构。以损坏的图像inpaint失踪的结构和纹理信息，基于小波分解的图像修补算法提出。首先损坏的图像分解成子图像和纹理结构，利用小波子图像转变。然后，地区结构中缺少的信息的子图像重建曲率驱动扩散（CDD），算法，而在同一区域的纹理子图像填写基于改进的纹理合成的典范 最后，恢复的图像，通过重组，结构和纹理恢复的结果。大量的实验表明，该算法可以快速，高效地恢复在同一时间的结构和纹理信息，视觉效果和峰值信噪比比（PSNR）比同类算法更好。(Image inpainting is an important problem image processing. It is a difficult problem to simultaneously fill-in the
texture and structure in regions of missing image information. In order to inpaint the damaged image with both
missing the structure and texture information, an image inpainting algorithm based on wavelet decomposition is
presented. First the damaged image is decomposed into structure sub-image and texture sub-image using the wavelet
transformation. Then, the sub-image with the region of missing information in the structure is reconstructed by
Curvature-Driven Diffusions (CDD) algorithm, while the same region in the texture sub-image is filled-in with the
improved texture synthesis based on exemplar Finally, the restored image is given by recombining the structure and
texture restored results. A large number of experiments show that the proposed algorithm can quickly and efficiently
restore the structure and texture information at the same time, and the visual eff)
- 2012-06-05 22:04:45下载
- 积分：1
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Image_Steg
Image Steganograpy using Pixel-Value Differencing
- 2012-10-10 16:39:03下载
- 积分：1
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vc++_image
这是图象处理模式识别一书的源代码，包括C++和MATLAB的程序，对于做这方面的研究人员来说，会很有帮助的。(This is an image processing pattern recognition on the source code, including C and Matlab procedures for doing this kind of research personnel, will be very helpful.)
- 2005-04-21 21:42:03下载
- 积分：1
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muller
由图片对应点数据计算穆勒矩阵，并对其进行极分解，求得其3个分项，同时计算其各项指标参数(The Muller matrix is calculated by the corresponding data of the image, and the polar decomposition is carried out to obtain the 3 sub items, and the index parameters are calculated at the same time)
- 2020-12-06 14:49:21下载
- 积分：1
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dx-4.4.4.tar
图像的纹理特征参数的灰度共生矩阵的计算，该方法效果好，速度快，易理解。(The image texture characteristic parameters GLCM calculation, the method effective, fast, easy to understand.)
- 2010-02-23 15:45:57下载
- 积分：1
