4.7 Article

Band Sampling for Hyperspectral Imagery

Journal

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGRS.2021.3102861

Keywords

Band sampling (BSam); iterative fixed uniform band sampling (FUBSam); iterative random band sampling (IRBSam); iterative uniform band sampling (UBSam); random band sampling (RBSam)

Funding

  1. Fundamental Research Funds for the Central Universities [3132019341]

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Band sampling (BSam) is an innovative concept for hyperspectral imaging derived from signal sampling in communications/signal processing and sampling theory in information theory. It differs from band selection (BSel) in that it samples bands with a fixed rate, has no specific means of band sampling, and requires no prior band knowledge compared to BSel. Two strategies for BSam have been developed, namely uniform band sampling (UBSam) and random band sampling (RBSam), which generally perform better than custom-designed BSel methods.
Band sampling (BSam) is an innovative concept for hyperspectral imaging, which is derived from signal sampling in communications/signal processing as well as sampling theory in information theory. It is quite different from band selection (BSel) in several aspects. First of all, BSam samples bands with a given fixed BSam rate (BSamR) as opposed to BSel, which selects appropriate bands according to the number of bands to be selected. Second, BSam requires no specific means of sampling bands compared to BSel, which requires a specific rule to select bands such as band prioritization (BP) criteria or band search strategies. Third, BSam samples bands without prior band knowledge or specific applications in contrast to BSel, which considers certain bands more significant than other bands according to various applications. Two strategies are developed for BSam. One is from information theory. Under a completely blind and unknown environment, the maximum entropy is achieved by the uniform distribution. This suggests that one best strategy for BSam is uniform band sampling (UBSam). Another strategy is random BSam (RBSam) analogous to random signal sampling in compressive sensing (CS) where the bands sampled by RBSam are random but are not deterministic like the bands selected by BSel. Interestingly, UBSam and RBSam generally perform better than custom-designed BSel methods. To illustrate its potential utility of BSam in various applications, target detection, anomaly detection, and image classification are studied through extensive experiments for demonstration.

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