A method for microscopic hyperspectral image mosaic based on RGB image layer feature localization and mosaicing

Feng Liu; Bo Long; Hui Chen

doi:10.1117/12.3026573

27 March 2024 A method for microscopic hyperspectral image mosaic based on RGB image layer feature localization and mosaicing

Feng Liu, Bo Long, Hui Chen

Author Affiliations +

Proceedings Volume 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023); 131052R (2024) https://doi.org/10.1117/12.3026573
Event: 3rd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 2023, Qingdao, China

Abstract

Research into early data collection is often neglected, despite the growing focus on micro hyperspectral imaging technology in the medical field. Unfortunately, the data obtained from a single micro hyperspectral image is often limited in scope, making it hard to extract features and analyze spectral data of healthy cells. To address the above issues, a micro hyperspectral image stitching method based on RGB image layer feature localization and stitching is proposed, Extract the collected data into three RGB bands, perform feature extraction on them, calculate the horizontal offset, and complete the matching and stitching of microscopic hyperspectral images based on the coordinate position relationship.By employing the mean filtering technique, data fusion can be accomplished, thus allowing for the stitching of hyperspectral images on the micro dimension for spectral information.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Feng Liu, Bo Long, and Hui Chen "A method for microscopic hyperspectral image mosaic based on RGB image layer feature localization and mosaicing", Proc. SPIE 13105, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2023), 131052R (27 March 2024); https://doi.org/10.1117/12.3026573

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KEYWORDS

Hyperspectral imaging

Matrices

Feature extraction

RGB color model

Image fusion

Tunable filters

Image processing

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