Viewing-distance aware super-resolution for high-definition display

Chih Tsung Shen, Hung Hsun Liu, Ming Hsuan Yang, Yi Ping Hung, Soo Chang Pei

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


In this paper, we propose a novel algorithm for high-definition displays to enlarge low-resolution images while maintaining perceptual constancy (i.e., the same field-of-view, perceptual blur radius, and the retinal image size in viewer's eyes). We model the relationship between a viewer and a display by considering two main aspects of visual perception, i.e., scaling factor and perceptual blur radius. As long as we enlarge an image while adjust its image blur levels on the display, we can maintain viewer's perceptual constancy. We show that the scaling factor should be set in proportion to the viewing distance and the blur levels on the display should be adjusted according to the focal length of a viewer. Toward this, we first refer to edge directions to interpolate a low-resolution image with the increasing of viewing distance and the scaling factor. After images are interpolated, we utilize a local contrast to estimate the spatially varying image blur levels of the interpolated image. We then further adjust the image blur levels using a parametric deblurring method, which combines L1 as well as L2 reconstruction errors, and Tikhonov with total variation regularization terms. By taking these factors into account, high-resolution images adaptive to viewing distance on a display can be generated. Experimental results on both natural image metric and user subjective studies across image scales demonstrate that the proposed super-resolution algorithm for high-definition displays performs favorably against the state-of-the-art methods.

Original languageEnglish
Article number6966784
Pages (from-to)403-418
Number of pages16
JournalIEEE Transactions on Image Processing
Issue number1
Publication statusPublished - 2015 Jan 1

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Graphics and Computer-Aided Design


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