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Article summary:
1. This article proposes a novel hyperspectral anomaly detection method for spectral anomaly targets based on spatial and spectral constraints (SASCs).
2. The proposed method suppresses the background and reduces the false alarm rate, while effectively reducing the missing detection rate.
3. The optimal order of fractional Fourier transform (FrFT) is determined by combining spatial anomaly results with the uncertainty principle, which is used in FrFT of HSI.
Article analysis:
The article provides a detailed overview of a novel hyperspectral anomaly detection method for spectral anomaly targets based on spatial and spectral constraints (SASCs). The article is well-written and provides an in-depth analysis of the proposed method, its advantages, and its potential applications. However, there are some potential biases that should be noted. For example, the article does not provide any evidence to support its claims about the effectiveness of the proposed method or any counterarguments to other methods that may be more effective. Additionally, it does not explore any possible risks associated with using this method or present both sides equally when discussing its advantages and disadvantages. Furthermore, there is no mention of any promotional content or partiality in the article which could lead to bias in favor of this particular method over others. All in all, while this article provides an interesting overview of a new approach to hyperspectral anomaly detection, it should be read with caution due to potential biases and lack of evidence for its claims.