Hyperspectral Data Processing: Algorithm Design and Analysis

7.5 Experiments

This section presents experimental studies on performance analysis of six SM-EEAs representing four different criteria, that is, PPI from convexity geometry via OP, N-FINDR and AN-FINDR from finding maximum simplex volume, SPCA-EEA from statistical correlation, FCLS-EEA from LSE-based fully abundance-constrained spectral unmixing, and AMEE from morphology. Three sets of experiments are conducted for performance evaluation, which are (1) six synthetic image-based scenarios discussed in Chapter 4, (2) AVIRIS and (3) HYDICE real image experiments. Since MNF is one of the most widely used techniques to perform DR in the literature, it is used for all EEAs that require DR.

7.5.1 Synthetic Image Experiments

The synthetic images used for experiments were the three scenarios of target implantation (TI), TI1, TI2, and TI3, and the three scenarios of target embeddedness, (TE), TE1, TE2, and TE3, are described in Chapter 4 and reproduced in Figure 7.12 for reference.

Figure 7.12 Three scenarios designed for TI, TI1, TI2, and TI3 and three scenarios of TE, TE1, TE2, and TE3.

Six SM-EEAs, MATLAB-PPI (PPI) with 500 skewers, 1-IN-FINDR, AN-FINDR, SPCA-EEA, FCLS-EEA, and AMEE, were implemented on these six scenarios to extract endmember pixels. Based on the ground truth in Figure 4.2 and Tables 4.1 and 4.2, there are 100 pure pixels, 20 mixed pixels, and 10 subpixels, all of which ...