An Approach for Implementing Electronic ImageStabilization Using an FPGA System

This paper proposes an approach for the implementation of a low-power electronic (digital) image stabilization using an AMD/Xilinx Zynq UltraScale+ ZU7EV device (CPU+FPGA) with a custom Linux OS. The stabilization method is based on frame-to-frame motion detection (Harris Corner Detector, an iterative optical flow calculator combined with a 4:2:1 down-sampler an 1:2:4 up-sampler) and an affine transformation that applies the stabilization. The scientific contribution of this paper resides in a combination of the most recent software algorithms presented in literature and porting that new resulting algorithm into hardware with the achieved performance of more than 2.5x current state of the art, thus enabling stabilization at 4K-UHD resolution.

Authors

Publication Details

Journal
Romanian Journal of Information Science and Technology
Published
2024-09-30
DOI
https://doi.org/10.59277/romjist.2024.3-4.02
Citations
1
Primary Topic
Image and Video Stabilization
Type
article
Field-Weighted Citation Impact
0.25
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article

An Approach for Implementing Electronic ImageStabilization Using an FPGA System

Călin Bîră, A. Ulmamei
1 citations
Romanian Journal of Information Science and Technology
Image and Video Stabilization
0.25
article

An Approach for Implementing Electronic ImageStabilization Using an FPGA System

Călin Bîră, A. Ulmamei
article en
1 citations

Abstract

This paper proposes an approach for the implementation of a low-power electronic (digital) image stabilization using an AMD/Xilinx Zynq UltraScale+ ZU7EV device (CPU+FPGA) with a custom Linux OS. The stabilization method is based on frame-to-frame motion detection (Harris Corner Detector, an iterative optical flow calculator combined with a 4:2:1 down-sampler an 1:2:4 up-sampler) and an affine transformation that applies the stabilization. The scientific contribution of this paper resides in a combination of the most recent software algorithms presented in literature and porting that new resulting algorithm into hardware with the achieved performance of more than 2.5x current state of the art, thus enabling stabilization at 4K-UHD resolution.

Romanian Journal of Information Science and TechnologyVol. 27(3-4)
Openalex Percentile: Top 46%
Image and Video Stabilization
0.25
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