A fast autoregression based image interpolation method

Zhe Wang, Jiefu Zhai, Mengchu Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Image interpolation techniques seek to convert low-resolution images into high-resolution ones. Conventional linear interpolation methods usually have difficulty in preserving local geometric structures. Autoregression model based interpolation methods could well exploit the dual geometry similarity between the coarse and fine scales and thus obtain better results. However, to compute the local autoregression coefficients may introduce tremendous computational complexity. In this paper, we aim to simplify this computation process by adaptively selecting the optimal interpolation filter that minimizes the autoregression energy function. The proposed scheme also makes use of the so-called integral images to reduce the computational complexity greatly and thus keeps the algorithm flexible and computationally efficient at the same time. Experimental results demonstrate that the proposed method has much less computational complexity while the visual quality is even better than the state-of-art autoregression method.

Original languageEnglish (US)
Title of host publicationProceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC
Pages1400-1404
Number of pages5
DOIs
StatePublished - Aug 18 2008
Event2008 IEEE International Conference on Networking, Sensing and Control, ICNSC - Sanya, China
Duration: Apr 6 2008Apr 8 2008

Publication series

NameProceedings of 2008 IEEE International Conference on Networking, Sensing and Control, ICNSC

Other

Other2008 IEEE International Conference on Networking, Sensing and Control, ICNSC
CountryChina
CitySanya
Period4/6/084/8/08

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering

Fingerprint Dive into the research topics of 'A fast autoregression based image interpolation method'. Together they form a unique fingerprint.

Cite this