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Article

Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching

Department of Electronics and Computer Engineering, Centre for Robotics and Intelligent Systems, University of Limerick, V94 T9PX Limerick, Ireland
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J. Mar. Sci. Eng. 2020, 8(6), 449; https://doi.org/10.3390/jmse8060449
Received: 21 May 2020 / Revised: 16 June 2020 / Accepted: 17 June 2020 / Published: 19 June 2020
(This article belongs to the Special Issue Underwater Computer Vision and Image Processing)
Feature extraction and matching is a key component in image stitching and a critical step in advancing image reconstructions, machine vision and robotic perception algorithms. This paper presents a fast and robust underwater image mosaicking system based on (2D)2PCA and A-KAZE key-points extraction and optimal seam-line methods. The system utilizes image enhancement as a preprocessing step to improve quality and allow for greater keyframe extraction and matching performance, leading to better quality mosaicking. The application focus of this paper is underwater imaging and it demonstrates the suitability of the developed system in advanced underwater reconstructions. The results show that the proposed method can address the problems of noise, mismatching and quality issues which are typically found in underwater image datasets. The results demonstrate the proposed method as scale-invariant and show improvements in terms of processing speed and system robustness over other methods found in the literature. View Full-Text
Keywords: underwater image; feature extraction; image matching; stitching; image mosaic underwater image; feature extraction; image matching; stitching; image mosaic
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MDPI and ACS Style

Abaspur Kazerouni, I.; Dooly, G.; Toal, D. Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching. J. Mar. Sci. Eng. 2020, 8, 449. https://doi.org/10.3390/jmse8060449

AMA Style

Abaspur Kazerouni I, Dooly G, Toal D. Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching. Journal of Marine Science and Engineering. 2020; 8(6):449. https://doi.org/10.3390/jmse8060449

Chicago/Turabian Style

Abaspur Kazerouni, Iman, Gerard Dooly, and Daniel Toal. 2020. "Underwater Image Enhancement and Mosaicking System Based on A-KAZE Feature Matching" Journal of Marine Science and Engineering 8, no. 6: 449. https://doi.org/10.3390/jmse8060449

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