Guided Filtering using Reflected IR Image for Improving Quality of Depth Image

Takahiro Hasegawa, Ryoji Tomizawa, Yuji Yamauchi, Takayoshi Yamashita, Hironobu Fujiyoshi

2016

Abstract

We propose the use of a reflected IR image as a guide image to improve the quality of depth image. Guided filtering is a technique that can quickly remove noise from a depth image by using a guide image. However, when an RGB image is used as a guide image, the quality of depth image does not be improved if the RGB image contains texture information (such as surface patterns and shadows). In this study, our aim is to obtain a depth image of higher quality by using a guide image derived from a reflected IR image, which have less texture information and a high correlation with depth image. Using reflected IR image, it is possible to perform filtering while retaining edge information between objects of different materials, without being affected by textures on the surfaces of these objects. In evaluation experiments, we confirmed that a guide image based on reflected IR image produce better denoising effects than RGB guide image. From the results of upsampling tests, we also confirmed that the proposed IR based guided filtering has a higher PSNR than that of RGB image.

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Paper Citation


in Harvard Style

Hasegawa T., Tomizawa R., Yamauchi Y., Yamashita T. and Fujiyoshi H. (2016). Guided Filtering using Reflected IR Image for Improving Quality of Depth Image . In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016) ISBN 978-989-758-175-5, pages 33-39. DOI: 10.5220/0005717800330039


in Bibtex Style

@conference{visapp16,
author={Takahiro Hasegawa and Ryoji Tomizawa and Yuji Yamauchi and Takayoshi Yamashita and Hironobu Fujiyoshi},
title={Guided Filtering using Reflected IR Image for Improving Quality of Depth Image},
booktitle={Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)},
year={2016},
pages={33-39},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005717800330039},
isbn={978-989-758-175-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2016)
TI - Guided Filtering using Reflected IR Image for Improving Quality of Depth Image
SN - 978-989-758-175-5
AU - Hasegawa T.
AU - Tomizawa R.
AU - Yamauchi Y.
AU - Yamashita T.
AU - Fujiyoshi H.
PY - 2016
SP - 33
EP - 39
DO - 10.5220/0005717800330039