Hyperspectral Data Processing: Algorithm Design and Analysis

21.4 Experiments for BP

As noted in the introduction, there are some important differences between BP and DP. One is that BP prioritizes individual spectral bands based on their contained information, whereas DP prioritizes spectral dimensions according to the information contained in their transformed components from the entire image data. Therefore, spectral bands only share information provided by interband correlation compared to spectral components that only retain information of residuals resulting from all their previous spectral components. Accordingly, BP and DP have different utilities in applications. This section presents applications of BP using different sets of prioritized spectral bands in unsupervised spectral unmixing and endmember extraction, which are not applicable to DP. The HYDICE image scene in Figure 1.15(a) and (b) was selected for experiments to allow us to perform a quantitative analysis in performance of unmixing panel pixels and extracting panel pixels as endmembers.

21.4.1 Applications Using Highest-Prioritized Bands

When it comes to BP, a natural and intuitive approach is to select bands that have the highest-priority scores. Table 21.2 tabulates the first 30 bands with highest-priority scores selected progressively by various BP criteria developed in Section 21.3 with a backslash “/” used to separate two selected bands. It is very clear to see from the table that if one spectral band is selected with a high-priority score, so are its neighboring ...