Analyzing the Effect of the Spectral Interference of Mixed Pixels Using Hyperspectral Imagery

The widespread presence of mixed pixels in remotely sensed images is a pressing challenge for accurate target detection and classification. Linear spectral mixture analysis (LSMA) is commonly used to address this problem by deriving remotely sensed information at the subpixel level. In the implementation of LSMA, the effects of mixed-pixel spectral interference need to be taken into account; mixed spectra would exhibit as a pure spectral characteristic when the abundance of one endmember in a mixed pixel exceeds a specific threshold. However, the thresholds of endmember abundance resulting in mixed-pixel spectral interference remain unclear. Thus, this study designed an experiment to analyze the effect of the spectral interference of mixed pixels and to identify the thresholds causing such interference by spectral similarity measures (spectral angle and spectral distance). Four types of pure endmember spectra (vegetation, high-albedo impervious surface (HIS), low-albedo impervious surface (LIS), soil) and corresponding representative mixed spectra with endmember abundances of 95%–5% at intervals of 5% were collected from Earth Observing-1 Hyperion imagery. Spectral similarity measures among the pure endmember spectra and representative mixed spectra were used to determine the thresholds of endmember abundance that cause spectral interference. The results verified the effect of the spectral interference of mixed pixels. The thresholds of abundance causing mixed-pixel spectral interference in vegetation, HIS, LIS, and soil endmembers were 70%, 75%, 80%, and 70%, respectively. Therefore, when the endmember abundance within mixed pixels exceeds the abovementioned thresholds, these mixed spectra are interfered and would exhibit as a pure spectral characteristic. Accordingly, interfered mixed pixels have to be removed before applying LSMA or other unmixing methods to avoid the effect of spectral interference.