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A non-iterative automated mechanism for image inpainting

机译:一种非迭代自动化机制,用于图像染色

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Portions of an image may be damaged or missing. Inpainting is required to recover the missing portions. Inpainting is cleaning off dirt, filling discolored sports, and repairing torn, warped, or cracked in a damaged image. The existing Navier-Stokes Partial Differential Equations (PDE) method for inpainting is iterative by nature, with a time variable serving as iteration parameter. For reasons of stability a large number of iterations can be needed which results in a computational complexity that is often too large for interactive image manipulation. A non-iterative automated mechanism for image inpainting is proposed. Colors are treated as fluid that flow or diffuse from the surrounding areas into the empty region. Gains ranging from 9.44 dB to 19.49 dB were obtained with the non-iterative automated inpainting scheme. The automated inpainting scheme overcomes the computational complexity associated with the existing Navier-Stokes PDE inpainting method, and is more suitable for interactive image manipulations.
机译:图像的部分可能会损坏或丢失。需要恢复缺失的部分需要修整。污垢正在清洁污垢,填充变色的运动,并在损坏的图像中修复撕裂,翘曲或破裂。现有的Navier-Stokes用于修复的偏微分方程(PDE)方法是迭代的,其时间变量用作迭代参数。出于稳定性的原因,可能需要大量的迭代,这导致计算复杂度通常太大而对于交互式图像操纵。提出了一种用于图像染色的非迭代自动化机制。颜色被视为从周围区域流入空区域的流体的流体。利用非迭代自动化批量计划获得9.44 dB至19.49 dB的收益。自动化批量方案克服了与现有的Navier-Stokes PDE初始化方法相关的计算复杂度,更适合交互式图像操纵。

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