Parallelizing maximum likelihood classification (MLC) for supervised image classification by pipelined thread approach through high-level synthesis (HLS) on FPGA cluster

Parallelizing maximum likelihood classification (MLC) for supervised image classification by pipelined thread approach through high-level synthesis (HLS) on FPGA cluster

High spectral, spatial, vertical and temporal resolution data are increasingly available and result in the serious challenge to process big remote-sensing images effectively and efficiently. This article introduced how to conduct supervised image classification by implementing maximum likelihood cla...

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Bibliographic Details
Main Authors: Sen Ma, Xuan Shi, David Andrews
Format: Article
Language:English
Published: Taylor & Francis Group 2018-04-01
Series:Big Earth Data
Subjects:
FPGA
maximum likelihood classification
parallel computing
Online Access:http://dx.doi.org/10.1080/20964471.2018.1470249

Internet

http://dx.doi.org/10.1080/20964471.2018.1470249

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