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采用M.Bertalmio and G.Sapiro论文中算法的图像修复C++代码。需要提供原始破损图像和破损区域的掩模图像,修复结果实时显示。-used Bertalmio and G. M. Sapiro papers algorithm for image restoration generation C yards. The need for the original image and damaged the damaged region mask images, results, real-time repair.
Date : 2026-01-16 Size : 1.22mb User : 屈磊

采用径向基函数进行图像修复的VC++源代码,用户可交互式地选择破损修复区域。-RBF used for image restoration VC source code, users can interactively choose to repair damaged region.
Date : 2026-01-16 Size : 1mb User : 屈磊

DL : 1
采用T.Chan的总体变分(TV)方法实现图像修复,由于算法本身的局限性,无法解决视觉连通性的问题。-using T. Chan of the overall variation (TV) method of image restoration, Due to the limitations of their own algorithm to solve visual connectivity problems.
Date : 2026-01-16 Size : 91kb User : ch

一个用visual c++ 写的图像修复算法,有界面可以直接编译运行-A use of visual c++ Write image restoration algorithm, there are interface can be directly compiled to run
Date : 2026-01-16 Size : 1.7mb User : dai

image inpainting -CS7495 Final Project Sooraj Bhat Object Removal by Exemplar-based Inpainting USING THE CODE Everything was done in Matlab and MEX (i.e. a C function callable from Matlab). First, the C code needs to be compiled. At the Matlab prompt, type: mex bestexemplarhelper.c You should then be able to run the following (which takes ~2mins on my 2GHz Pentium 4 laptop with 256MB of RAM): [i1,i2,i3,c,d,mov] = inpaint( bungee0.png , bungee1.png ,[0 255 0]) A smaller run (~25 seconds) would be: [i1,i2,i3,c,d,mov] = inpaint( bw0.png , bw2.png ,[0 255 0]) To visualize: plotall close movie(mov) SAMPLE IMAGES & RESULTS *0.png The original images ( bw and bungee ) *{1,2}.png The different fill region masks. *P2.png Plots of confidence and data terms. *P5.png Plots of original, fill region, inpainted images and confidence and data terms. Other images in the dir contain redundant information. I di
Date : 2026-01-16 Size : 1.69mb User : majb

Inpaint over missing data in N-D arrays
Date : 2026-01-16 Size : 4kb User : Kuo
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