一种基于损伤区域信息的图像修复方法

Guoyue Chen, Xingguo Zhang, Kazutaka Nakui, Kazuki Saruta, Yuki Terata, Min Zhu
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引用次数: 1

摘要

随着数字图像处理技术的发展,图像补漆已成为一种令人印象深刻和实用的技术。基于偏导数方程或纹理合成,人们提出了许多图像填充技术。Amano等人提出了一种基于特征空间分析的方法,称为Lost Pixels的Back Projection (BPLP)。从原始图像的一组学习样本中获取特征空间,然后通过逆投影和特征空间的线性组合估计缺失区域。但修复后损伤部位周围仍有明显的不适。在本文中,我们提出了一种自适应的BPLP算法,该算法在具有自然缺陷的图像上表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Image Inpainting Method Using Information of Damage Region
With the development of digital images processing, image inpainting is become one of the most impressive and useful technique. Based on partial derivative equations or texture synthesis, many image inpainting techniques have been proposed. Amano et al. proposed a method that based on eigenspace analyzes, which is called Back Projection for Lost Pixels (BPLP). It obtains the eigenspace from a set of learning samples from original image, then estimating the missing region by inverse projection and a linear combination of the eigenspace. But it remains have some obvious discomfort surrounding the damage region after restoration treatment. In this paper, we have proposed an adaptation of BPLP algorithms, which are performing well on images with natural defects.
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