An oblique subspace projection approach for mixed pixel classification in hyperspectral images

✍ Scribed by Te-Ming Tu; Hsuen-Chyun Shyu; Ching-Hai Lee; Chein-I Chang

• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 430 KB
• Volume: 32
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(98)00165-4

✦ Synopsis

Recently oblique projection has been studied for many applications in signal processing. In this paper, the concept of oblique projection is applied to develop an algorithm for hyperspectral image classi"cation. Compared with the orthogonal subspace projector (OSP), it can be found that OSP is a priori classi"er but the oblique subspace projection classi"er will be referred to a posterior. As a consequence, the oblique subspace projector (OBP) can be thought of as a generalized classi"er including OSP. Furthermore, the estimation error from the OBP can be evaluated by applying the Neyman}Pearson detection theory to the corresponding receiver operating characteristic (ROC) curve so the accuracy of the classi"cation can be calculated thereafter. Finally, some computer simulations using real airborne visible infrared image spectrometer (AVIRIS) data are accomplished to justify and compare the e!ectiveness of the above algorithms.