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April 23, 2026Journal of Spectroscopy0 citationsOpen Access

Comparative Study on Hyperspectral Unmixing Errors Considering Preprocessing Differences

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HZHaonan ZhangSWShihai WuJZJing Zhang

Key Points

  • The study aims to evaluate how different preprocessing methods impact the accuracy of hyperspectral unmixing.
  • Fabricated mixed pixel samples with varying black-to-white ratios.
  • Applied eight preprocessing methods grouped into four categories.
  • Used the constrained linear spectral mixture model to analyze unmixing accuracy via RMSE and AE.
  • SG and MA methods achieve the lowest RMSE of 0.021, preserving original spectral features.
  • MSC method shows the lowest unmixing accuracy with an RMSE of 0.531.
  • AE shows significant increases with higher black proportions, while MA and SG maintain stability with minor fluctuations.

Abstract

Before conducting the unmixing of mixed pixels, the question of how to preprocess the original spectral data is a controversial issue. Mixed pixel samples with varying black‐to‐white ratios were fabricated, and their original spectral data were acquired using an ASD FieldSpec3 spectrometer in a laboratory setting. The eight commonly used preprocessing methods were divided into four groups: baseline correction (first derivative FD and second derivative SD), scattering correction (multivariate scattering correction MSC and standard normal variate SNV), smoothing (moving average MA and Savitzky–Golay SG), and scaling (maximum normalization MN and deviation standardization DS). The constrained linear spectral mixture model (CLSMM) was employed to unmix the original spectra and the preprocessed spectra, and the influence of preprocessing on unmixing was quantitatively analyzed by using the root‐mean‐square error (RMSE) and abundance error (AE). The results show the following: (1) the spectral signatures of mixed pixels are altered by the choice of preprocessing method. The SG and MA remain consistent with the original spectra. However, the spectral curve after DS processing approaches a straight line. (2) MSC has the lowest unmixing accuracy, with an RMSE of 0.531. Smoothing processing reduces the amount of spectral data while retaining the original spectral features. The RMSE of SG and MA is only 0.021. (3) By analyzing the abundance differences of different mixed pixel samples, it was found that as the black proportion within the pixel increases, the AE of most preprocessing methods shows a significant upward trend. However, MA and SG exhibit minor fluctuations, and the abundance difference is only 0.018. The results of this study establish a statistical foundation to guide the selection of appropriate preprocessing methods.

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Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/69e9bb6285696592c86ed0edhttps://doi.org/10.1155/jspe/9709553
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