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Partial Demosaicing for Stereo Matching of CFA Images on GPU and CPU

Authors:
Naiyu Zhang
Jean-Charles Créput
Hongjian Wang
Cyril Meurie
Yassine Ruichek

Keywords: GPU, Demaosaicing Stereovision, CFA Image, CUDA

Abstract:
This paper presents a GPU implementation of a partial demosaicing scheme that is specially designed for stereo matching of CFA image. This method consists of three main techniques keys: the adapted matching cost for CFA image, the estimated Second color component based on Hamilton’s estimate method and a robust cost aggregation window. Experiments are carried out to explore the performance for this method on GPU both at matching quality and matching efficiency, with comparison with version on CPU. The experiments on different size image pairs from Middlebury dataset show that this method can be substantially accelerated on GPU when the image size is large and has still space for improvements in performance.

Pages: 33 to 38

Copyright: Copyright (c) IARIA, 2013

Publication date: November 17, 2013

Published in: conference

ISSN: 2308-3484

ISBN: 978-1-61208-310-0

Location: Lisbon, Portugal

Dates: from November 17, 2013 to November 21, 2013