Rapid Classification of Mixed Hyperspectral Data by ROAA SVM

Capturing of high resolution hyperspectral images is one of the most expensive tasks in imaging industry. The main problem of low resolution hyperspectral data is the classificationof pixels where more than one land cover type lie in one pixel, called a mixed pixel. To resolve this issue, methods composed ofhard and soft classification techniques have shown good results. For rapid classification of these mixed hyperspectral images, wepropose to use Reduced OAA SVM combined with spectral mixture analysis at sub-pixel level and a fast post processing stepto eliminate unwanted solitary mappings. Experiments conducted over a common hyperspectral image show great improvements in terms of overall classification accuracy and computation time.

Keywords:

hyperspectral data , mixed pixels , image classification , source separation , ROAA SVM , spectral mixture analysis