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

    ASJC Scopus subject areas

    • Signal Processing
    • Electrical and Electronic Engineering

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  • 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