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Image enlargement method based on cubic surfaces with local features as constraints

机译：基于局部特征为约束的三次曲面的图像放大方法

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摘要

The quality of image edges and textures plays a vital role in the visual effect of images. For keeping the features of image edges and textures better, we propose an image enlargement method based on cubic fitting surfaces with local features as constraints. The cubic fitting surface constructed with the edge and the distance as constraints effectively improves the approximation accuracy and shape retention, resulting in sharper edges in the initially enlarged image. The error between the cubic fitting surface and the input image surface leads to the error between the initially enlarged image and the input image. Using image self-similarity to filter the initially enlarged image can further improve its quality. In the iterative optimization process, the cubic surface with higher fitting accuracy is constructed on smaller regions of low resolution error images, which effectively improves the quality of the enlarged image and accelerates the convergence speed. Because the algorithm effectively utilizes the local feature information, compared with other state-of-the-art methods, the new method not only has higher PSNR/SSIM in numerical accuracy, but also has clear edges and textures visually. (C) 2019 Elsevier B.V. All rights reserved.
机译：图像边缘和纹理的质量在图像的视觉效果中起着至关重要的作用。为了更好地保持图像边缘和纹理的特征，我们提出了一种以局部特征为约束的三次拟合曲面为基础的图像放大方法。以边缘和距离为约束构造的三次拟合曲面有效地提高了近似精度和形状保持性，从而在最初放大的图像中产生了更清晰的边缘。三次拟合表面和输入图像表面之间的误差导致初始放大图像和输入图像之间的误差。使用图像自相似性来过滤最初放大的图像可以进一步提高其质量。在迭代优化过程中，在较小分辨率的低分辨率误差图像区域上构建了拟合精度较高的三次曲面，有效提高了放大图像的质量，加快了收敛速度。因为该算法有效地利用了局部特征信息，所以与其他现有技术相比，该新方法不仅在数值精度上具有更高的PSNR / SSIM，而且在视觉上具有清晰的边缘和纹理。 （C）2019 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Signal processing》 |2020年第1期|107266.1-107266.12|共12页
  • 作者

    Liu Yepeng; Li Xuemei; Zhang Xin; Zhang Caiming;

  • 作者单位

    Shandong Univ Sch Software Jinan 250101 Shandong Peoples R China;

    Shandong Univ Sch Software Jinan 250101 Shandong Peoples R China|Shandong Coinnovat Ctr Future Intelligent Comp Yantai 264025 Peoples R China;

    Hangzhou Dianzi Univ Sch Comp Sci & Technol Hangzhou 310018 Zhejiang Peoples R China;

    Shandong Univ Sch Software Jinan 250101 Shandong Peoples R China|Digital Media Technol Key Lab Shandong Prov Jinan 250014 Shandong Peoples R China|Shandong Coinnovat Ctr Future Intelligent Comp Yantai 264025 Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Local feature; Cubic fitting surface; Quadratic polynomial patch; Iterative optimization;

    机译：本地特征;三次拟合表面;二次多项式补丁迭代优化;

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