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Radial Based Analysis of GRNN in Non-Textured Image Inpainting

机译:非纹理图像染色中GRNN的径向分析

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摘要

Image inpainting algorithms are used to restore some damaged or missing information region of an image based on the surrounding information. The method proposed in this paper applies the radial based analysis of image inpainting on GRNN. The damaged areas are first isolated from rest of the areas and then arranged by their size and then inpainted using GRNN. The training of the neural network is done using different radii to achieve a better outcome. A comparative analysis is done for different regression-based algorithms. The overall results are compared with the results achieved by the other algorithms as LS-SVM with reference to the PSNR value.
机译:图像批量算法用于基于周围信息恢复图像的一些损坏或丢失的信息区域。本文提出的方法适用于GRNN上的图像染色的基于径向分析。损坏的区域首先从区域的剩余部分隔离,然后按其尺寸排列,然后使用GRNN染色。使用不同的半径完成神经网络的培训以实现更好的结果。对不同回归的算法进行了比较分析。将整体结果与其他算法作为LS-SVM的结果进行比较,参考PSNR值。

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