17.4 Synthetic Image Experiments

Two of six synthetic image-based scenarios in Chapter 4, TI2 in Section and TE2 in Section, are particularly selected for experiments and re-described as follows.

Target Implantation 2

The target implantation 2 (TI2) inserts a number of panel pixels into the image by replacing their corresponding BKG pixels. So, the resulting synthetic image has clean panel pixels with perfect knowledge implanted in a noisy BKG corrupted an additive Gaussian noise with a certain level of SNR. TI2 is primarily designed to simulate scenarios with pure pixels implanted as pure signatures to represent true endmembers to evaluate the quantitative performance of SLSMA.

Target Embededness 2

As opposed to TI, the second type of target insertion is target embededness 2 (TE2) that is the same as the TI2 described above except the way the panel pixels are inserted. The BKG pixels were not removed to accommodate the inserted panel pixels as they are done in TI2, but were rather superimposed over the inserted panel pixels. So, in this case, the resulting synthetic image has clean panel pixels embedded in a noisy BKG. The TE2 is particularly designed to simulate scenarios where there are no pure pixels present in the data. As a result, no real true endmembers can be used for LSMA. So, TE2 is more realistic than TI2. Instead, the VSs must be found from TE2. Nevertheless, the complete knowledge of inserted panels and BKG signature is still available for quantitative ...

Get Hyperspectral Data Processing: Algorithm Design and Analysis now with O’Reilly online learning.

O’Reilly members experience live online training, plus books, videos, and digital content from 200+ publishers.