Generalized adaptive spatio-temporal auto-regressive model for video sequence restoration

Seok Joo Doo, Moon Gi Kang

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

In this paper, a generalized auto-regressive(AR) model is proposed for linear prediction based on adaptive spatio-temporal support region(ASTSR). The conventional AR model has the drawback that the prediction error increases in the edge region because the rectangular support region of the edge does not satisfy the stationary assumption. Thus the proposed approach puts an emphasis on the formulation of an adaptive spatio-temporal support region for the AR model called ASTSR. The ASTSR consists of two parts: 1) an adaptive spatial support region(ASSR) composed of pixels that are highly correlated with the current predicted pixel. 2) an adaptive temporal support region(ATSR) formed based on the existence of motion. The proposed AR model not only produces more accurate model parameters but also reduces the computational complexity in the motion picture restoration.

Original languageEnglish
Pages185-188
Number of pages4
Publication statusPublished - 1999
EventInternational Conference on Image Processing (ICIP'99) - Kobe, Jpn
Duration: 1999 Oct 241999 Oct 28

Other

OtherInternational Conference on Image Processing (ICIP'99)
CityKobe, Jpn
Period99/10/2499/10/28

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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  • Cite this

    Doo, S. J., & Kang, M. G. (1999). Generalized adaptive spatio-temporal auto-regressive model for video sequence restoration. 185-188. Paper presented at International Conference on Image Processing (ICIP'99), Kobe, Jpn, .