Analysis of noise impact on geo-object recognition in infrared bands using simulated data

Infrared spectrums play an important role in the information extraction of rock and minerals. Spectrum simulation is a fundamental issue of land surface scene simulation and image simulation of remote sensing systems. Signal to Noise Ratio is regarded as an essential parameter of instrument and remote sensing image. In this study, we used MODTRAN to simulate apparent radiance and different levels of additive white Gaussian noise was added to the simulated spectrum. In the section of noise impact on object recognition, Spectral Feature Fitting was chosen to compare the fit of simulated spectra with different noise levels to reference apparent radiance spectra without noise. Relative error is also calculated for the accuracy assessment which is helpful for validation and improvement of instrument parameters.