Progressive Band Processing of Linear Spectral Unmixing for Hyperspectral Imagery

摘要

This paper develops a new approach, called progressive band processing (PBP) of linear spectral unmixing (LSU) which can process data unmixing according to band sequential (BSQ) format. This new concept is quite different from band selection (BS) which must select bands from a fully collected band set based on a band optimization criterion. There are several advantages of using PBP-LSU over BS. In particular, it allows users to perform LSU using available bands without waiting for a complete collection of full bands. In doing so, an innovations information update equation is further derived and can process LSU as its band process is ongoing. To be more specific, LSU can be carried out by PBP by updating unmixed data recursively band by band in the same way that a Kalman filter does for updating data information in a recursive fashion. With such a recursion in nature, PBP is able to process bands of interest which may vary with different applications.