Subpixel Mapping Based on Hopfield Neural Network With More Prior Information

Affiliation of Author(s):电子信息工程学院

Journal:IEEE GEOSCIENCE AND REMOTE SENSING LETTERS

Key Words:Hopfield neural network (HNN) prior information remote sensing image subpixel mapping (SPM)

Abstract:Subpixel mapping based on the Hopfield neural network (HNN) is a technique to handle mixed pixels for obtaining the spatial distribution information of land cover. However, the original low-resolution remote sensing image may contain some uncertainties, such as the diversity of the land cover classes and the limitation of the resolution of the satellite sensor, the existing HNN is unable to fully utilize the prior information of the original image. In order to resolve this problem, an improved HNN (I-HNN) is proposed in this letter. In the proposed I-HNN, additional prior information of the original image is supplied by adding a new processing path to the existing HNN. To validate the effectiveness of the proposed method, two experiments are conducted on real hyperspectral images. The obtained results demonstrate that the proposed I-HNN outperforms the existing HNN. Moreover, the I-HNN does not require any auxiliary data.

ISSN No.:1545-598X

Translation or Not:no

Date of Publication:2019-08-01

Co-author:Wang, Liguo,Leung, Henry,ZHANG Gong

Correspondence Author:王鹏

Date of Publication:2019-08-01