公开(公告)号：US20190392261A1

公开(公告)日：2019-12-26

申请号：US16099140

申请日：2017-02-21

Applicant: SHANDONG UNIVERSITY

Inventor： Zhi LIU ,  Mingyu NIE ,  Qingchen QIU ,  Yulin SUN

IPC: G06K9/62 ,  G06F17/16

Abstract: The present invention discloses an end-member extraction method based on segmented VCA, comprising: conducting rough segmentation on a hyperspectral image by using an unsupervised classification method to partition image elements having a similar substance into the same block; conducting end-member extraction on an area in each partitioned block by using VCA, inverting the abundance by using a least square method after the end-member extraction, and determining one main end-member for each block according to the abundance value; and extracting the main end-members in all blocks and forming an end-member matrix of a global image. In the present invention, the VCA end-member extraction method is used in relatively simple partitioned environment blocks, and the main end-members in the blocks are then controlled by using the abundance inversion result feedback in the blocks, so as to prevent missing main end-members.