Hyperspectral linear unmixing: Quantitative evaluation of novel target design and edge unmixing technique

Abstract

Remotely sensed hyperspectral images (HSI) have the potential to provide large amounts of information about a scene. HSI, in this context, are images of the Earth collected with a spatial resolution of 1m to 30m in dozens to hundreds of contiguous narrow spectral bands over different wavelengths so that each pixel is a vector of data. Spectral unmixing is one application which can utilize the large amount of information in HSI. Unmixing is a process used to retrieve a material's spectral profile and its fractional abundance in each pixel since a single pixel contains a mixture of material spectra. Unmixing was used with images collected during an airborne hyperspectral collect at the Rochester Institute of Technology in 2010 with 1m resolution and a 390nm to 2450nm spectral range. The goal of our experiment was to quantitatively evaluate unmixing results by introducing a novel unmixing target. In addition, a single-band, edge unmixing technique is introduced with preliminary experimentation which showed results with mean unmixing fraction error of less than 10%. The results of the methods presented above helped in the design of future collection experiments.