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| Multi-Exposure Cumulative Fusion Algorithm for an Echelle Spectrometer |
| WU Rui-peng1, SUN Ya-nan1, WANG Lei2, LIU Jia1, NI Yun-ling1, YIN Lu1* |
1. College of Optical and Electronic Science and Technology, China Jiliang University, Hangzhou 310018, China
2. Hangzhou KemisIoT Sensor Technology Co., Ltd., Hangzhou 310018, China
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Abstract The echelle spectrometer, known for its high spectral resolution, is highly sensitive to environmental disturbances, with even minor fluctuations capable of inducing spot drift. Ensuring reliable spectral analysis, therefore, requires precise localization of the spot centroid. However, the instrument's wide dynamic range and broad spectral coverage pose challenges for conventional single-exposure methods, which often fail to exploit the detector's capacity while avoiding signal saturation fully. To overcome these limitations, this study introduces a multi-exposure cumulative fusion method for spectral acquisition and processing. Spectra are automatically captured at varying exposure times, filtered to retain valid frames, and subsequently merged with threshold-based processing to achieve both denoising and accurate centroid identification. Experimental results confirm that the proposed approach effectively prevents overexposure, reduces noise interference, and enables accurate spot signal detection. Compared to traditional high dynamic range acquisition methods, the proposed approach offers the advantage of balancing weak signal detection and preventing strong signal saturation. This work provides a robust and automated solution for advancing spectral data acquisition and processing.
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Received: 2025-05-22
Accepted: 2025-09-10
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Corresponding Authors:
YIN Lu
E-mail: yinlu890622@163.com
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