Hyperspectral Data Processing: Algorithm Design and Analysis

28.5 Computer Simulations Using NIST-Gas Data

In order to demonstrate the utility of KFSSE in spectral estimation, identification, and quantification, the spectral signature vectors in the data set Δ to be used for experiments were those in Figure 1.10 available at the National Institute of Standard Technology (NIST)'s website http://www.nist.gov/srd/nist35.htm. It contains nine agent signatures , eight of them, are composed of 880 bands, and only one of them, s₁, consists of 825 bands.

As mentioned previously, since KFSCSP technique developed in this chapter is signature a vector-based and not an image-based technique, KFSSE, KFSSI, and KFSSQ are not designed for classification. Therefore, their performance will be evaluated by signature vector-based spectral measures such as SAM and SID rather than image classifiers.

28.5.1 KFSSE

To implement KFSSE, the system gain c_l in (28.5) was set to be 1 for all , the standard deviation of the state noise v, σ_v, was empirically set to 10³ and the standard deviation of the measurement noise u, σ_u, was chosen to make SNR = 30 dB, where the SNR was defined before. It should be noted that throughout our extensive experiments, the results demonstrated ...