通过无数据库纹理合成的超分辨率

Yi-Chun Lin, Yi-Nung Liu, Shao-Yi Chien
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引用次数: 1

摘要

图像超分辨率在过去的几十年里得到了广泛的研究。在本文中,我们提出了一种超分辨率算法,该算法可以提供具有丰富细节和锐利边缘的逼真输出图像。本文的主要贡献是开发了一种无数据库的纹理合成技术。基于自然图像的分形特性,可以在低分辨率输入图像本身中找到合适的高分辨率斑块。上采样的双插值框架和最终优化的重构约束结合纹理合成构成了整个超分辨率算法。实验结果表明,本文提出的超分辨率算法比以往的无数据库超分辨率算法性能更好,耗时更短。1
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Super resolution via database-free texture synthesis
Image super resolution has been extensively investigated in the past decades. In this paper, we propose a super resolution algorithm which can provide vivid output image with rich details and sharp edges. The main contribution of this paper is the development of a database-free texture synthesis technique. Based on the fractal property of nature images, it is possible to find proper high-resolution patches in low-resolution input image itself. The double interpolation framework for up-sampling and the reconstruction constraint for the final optimization combined with the texture synthesis form the whole super resolution algorithm. Experimental results show that the proposed super resolution algorithm performs better and costs less time than other previous database-free super resolution works. 1
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