Image super-resolution with facet improvement and detail enhancement based on local self examples

He Jiang, Zaichen Cong, Zhiyong Gao, Xiaoyun Zhang
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引用次数: 1

Abstract

In this paper, an algorithm named ILSE (Improved Local Self Examples) is proposed to improve the facet phenomenon based on [1]. The algorithm divides the high frequency component into two orthogonal spaces by analyzing the covariance matrix of a single image. Moreover, the high resolution image can be further improved by using the IWLS (Improved Weighted Least Square) filter, in which we add one more regulation term to balance the gradient field and 2-order holomorphic complete differential form of the image. The algorithm can preserve the edge sharpness and enhance the details at the same time. Analysis is given on the relations and the differences between the proposed approach and some other state-of-the-art interpolation methods. Experimental results show that the proposed method can achieve better image quality as compared to other competitors.
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基于局部自例子的面改进和细节增强图像超分辨率
本文在[1]的基础上,提出了一种改善facet现象的算法ILSE (Improved Local Self Examples)。该算法通过分析单幅图像的协方差矩阵,将高频分量划分为两个正交空间。此外,采用改进加权最小二乘(IWLS)滤波器可以进一步提高图像的高分辨率,该滤波器增加了一个调节项来平衡梯度场和图像的二阶全纯完全微分形式。该算法在保持边缘清晰度的同时,还能增强图像的细节。分析了该方法与其他一些最新插值方法之间的关系和差异。实验结果表明,与其他竞争对手相比,该方法可以获得更好的图像质量。
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