Hyperspectral Data Processing: Algorithm Design and Analysis

18.4 Pixel Information Analysis via Synthetic Images

As mentioned above, the three categories of seven algorithms described in Section 18.3 represent different ways of generating target pixels, which can be characterized by the proposed four types of pixels. In this section, a comprehensive synthetic image-based study on pixel information analysis will be conducted to evaluate these seven algorithms on the basis of what types of pixels these algorithms really extract in terms of pure (or purest) pixels, mixed pixels, homogenous pixels, and anomalous pixels. The importance and significance of this study is to allow us to simulate various scenarios to evaluate subtle differences among the four different types of pixels, and to further explore the pixel information extracted by these three categories of algorithms for performance analysis. The reflectance spectra of five mineral spectra, alunite, buddingtonite, calcite, kaolinite, and muscovite, obtained from the USGS and shown in Figure 1.7 are first used for computer simulations.

A uniform background image with size of pixels was simulated by 100% of the same mixed signature (50% alunite and 50% kaolinite). Next, three sets of panels shown in Figure 18.1(a), that is, , , and for , were simulated by each of three signatures, buddingtonite, ...