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Finite Element Based Interpolation Methods for Spatial and Temporal Resolution Enhancement for Image Sequences.

机译：基于有限元的插值方法，用于图像序列的时空分辨率增强。

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摘要

Spatial resolution enhancement is a process for reconstructing a high resolution image from a low resolution image, whereas temporal resolution enhancement of encoded video aims of interpolating the skipped frames, making use of two successively received frames. In this thesis, a new image interpolation model, called the generalized image interpolation model, is developed in order to devise new techniques for spatial resolution enhancement of images, and temporal resolution enhancement of encoded video sequences. The interpolation model is based on the finite element method, and takes into account the unknown neighboring pixels, and therefore is capable of interpolating a collection of unknown pixels with an arbitrary shape, while providing a spatial continuity between the unknown pixels.;Next, error concealment-based MCI schemes are also presented for temporal resolution enhancement of encoded video sequences. These schemes are also based on the generalized image interpolation model, and need no pixel classification, thus reducing substantially the computational complexity. They are shown to be capable of concealing the errors in the homogeneous regions as well as in regions containing sharp edges. Experiments are carried out showing that the proposed schemes result in reconstructed frames having a better visual quality and a lower computational complexity than that provided by the existing techniques.;Based on the generalized interpolation model, an edge-preserving iterative refinement scheme for spatial resolution enhancement of images is proposed. This scheme exploits not only the neighboring pixels whose values are known, but also takes into account those with unknown values. It is shown that the edge-preserving iterative refinement process maintains the smooth variation along a dominant edge in the up-scaled image. Simulation results show that the proposed scheme results in up-scaled images with subjective and objective qualities, which are better than those of the existing interpolation schemes. Further, the scheme is also shown to be capable of up-scaling an image by an arbitrary magnification factor, without resorting to extra steps, or the use of any conventional interpolation method.
机译：空间分辨率增强是用于从低分辨率图像重建高分辨率图像的过程，而编码视频的时间分辨率增强的目的是利用两个连续接收的帧对跳过的帧进行插值。本文提出了一种新的图像插值模型，称为广义图像插值模型，目的是为图像的空间分辨率增强和编码视频序列的时间分辨率增强设计新技术。插值模型基于有限元方法，并考虑了未知的相邻像素，因此能够以任意形状插值未知像素的集合，同时在未知像素之间提供空间连续性。还提出了基于隐蔽的MCI方案，以提高编码视频序列的时间分辨率。这些方案也基于广义图像插值模型，不需要像素分类，因此大大降低了计算复杂度。它们显示出能够掩盖均匀区域以及包含尖锐边缘的区域中的误差。实验表明，与现有技术相比，所提出的方案具有更好的视觉质量和更低的计算复杂度。基于广义插值模型，提出了一种边缘保留的迭代细化方案，用于空间分辨率的增强。建议使用图像。该方案不仅利用其值已知的相邻像素，还考虑了具有未知值的像素。结果表明，保留边缘的迭代细化过程在放大图像中沿主边缘保持了平滑的变化。仿真结果表明，所提出的方案产生了具有主观和客观质量的放大图像，优于现有的插值方案。此外，该方案还显示出能够以任意放大倍数放大图像，而无需借助额外的步骤，也无需使用任何常规的插值方法。

著录项

  • 作者

    Wu, Yan.;

  • 作者单位

    Concordia University (Canada).;

  • 授予单位 Concordia University (Canada).;
  • 学科 Engineering Electronics and Electrical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 125 p.
  • 总页数 125
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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