November 2022
Intermediate
608 pages
21h 38m
English
Content preview from Advances in Hyperspectral Image Processing Techniques
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5Band Subset Selection for Hyperspectral Imaging
Chein‐I Chang
Center for Hyperspectral Imaging in Remote Sensing (CHIRS), Information and Technology College, Dalian Maritime University, Dalian, China
Remote Sensing Signal and Image Processing Laboratory, Department of Computer Science and Electrical Engineering, University of Maryland Baltimore County, Baltimore, MD, USA
5.1 Introduction
A brief review on band selection (BS) is already given in Chapter 4. This chapter begins with how multiple bands are selected via search algorithms which are absent in BS. Since simultaneous multiple band selection (SMBS) selects multiple bands “simultaneously,” it requires the prior knowledge of bands to be selected, nBS, in advance. Suppose that the full band set is given by Ω = {B1, B2, …, BL} where L is the total number of bands, 
is the selected jth band. Let nBS = p and 
be a band subset selected from Ω. In order to find a set of optimal multiple bands, 
, it must exhaust all possible p‐band combinations among L bands, which are 
possibilities. Practically speaking, this is impossible in reality. ...
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