Sub-pixel shift estimation of image based on the least squares approximation in phase region

Ryo Fujimoto, Takanori Fujisawa, Masaaki Ikehara

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

Abstract

This paper proposes a novel method to estimate noninteger shift of images based on least squares approximation in the phase region. Conventional methods based on Phase Only Correlation (POC) take correlation between a image and its shifted image, and then estimate the non-integer shift by fitting the model equation. The problem with using POC is that the true peak of the POC function may not match the estimated peak of the fitted model equation. This causes error in non-integer shift estimation. By calculating directly in the phase region, the proposed method allows the estimation of decimal shift through least squares approximation. Also by utilizing the characteristics of the natural image, the proposed method limits adoption range for least squares approximation. By these improvements, the proposed method improves the estimation and achieves high accuracy.

Original languageEnglish
Title of host publication2016 24th European Signal Processing Conference, EUSIPCO 2016
PublisherEuropean Signal Processing Conference, EUSIPCO
Pages91-95
Number of pages5
Volume2016-November
ISBN (Electronic)9780992862657
DOIs
Publication statusPublished - 2016 Nov 28
Event24th European Signal Processing Conference, EUSIPCO 2016 - Budapest, Hungary
Duration: 2016 Aug 282016 Sep 2

Other

Other24th European Signal Processing Conference, EUSIPCO 2016
CountryHungary
CityBudapest
Period16/8/2816/9/2

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ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

Cite this

Fujimoto, R., Fujisawa, T., & Ikehara, M. (2016). Sub-pixel shift estimation of image based on the least squares approximation in phase region. In 2016 24th European Signal Processing Conference, EUSIPCO 2016 (Vol. 2016-November, pp. 91-95). [7760216] European Signal Processing Conference, EUSIPCO. https://doi.org/10.1109/EUSIPCO.2016.7760216