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Open Access An efficient motion correction method for frequency-domain images based on Fast Robust Correlation

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Motion artifact suppression is an important task in the medical imaging field. Motion during data acquisition can produce blurred images and artifacts. The calculation load for previous motion correction methods is relatively high. In order to decrease computational complexity, an efficient motion correction method is proposed based on fast robust correlation. Fast robust correlation is a computationally efficient search algorithm for translational image matching in the frequency domain. This method calculates the matching surface using a series of high-speed correlations by defining a kernel with sinusoidal terms. The proposed method corrects motion distorted images by aligning translational motion between images formed by neighboring frequency segments. Due to the ineffectiveness of the squared difference kernel to detect motion between partial-Fourier images, the absolute value kernel is proposed, which can be easily approximated by sinusoidal terms. Total variation of the sum of partial-Fourier images is chosen as the new match criterion. FFTs are used to calculate correlations for computational speed. Experimental results show that the proposed method can reduce image motion artifacts effectively and efficiently.
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Keywords: Motion correction; absolute value kernel; fast robust correlation; image match

Document Type: Research Article

Publication date: January 13, 2019

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  • For more than 30 years, the Electronic Imaging Symposium has been serving those in the broad community - from academia and industry - who work on imaging science and digital technologies. The breadth of the Symposium covers the entire imaging science ecosystem, from capture (sensors, camera) through image processing (image quality, color and appearance) to how we and our surrogate machines see and interpret images. Applications covered include augmented reality, autonomous vehicles, machine vision, data analysis, digital and mobile photography, security, virtual reality, and human vision. IS&T began sole sponsorship of the meeting in 2016. All papers presented at EIs 20+ conferences are open access.

    Please note: For purposes of its Digital Library content, IS&T defines Open Access as papers that will be downloadable in their entirety for free in perpetuity. Copyright restrictions on papers vary; see individual paper for details.

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