Demosaicing for RGBZ sensor

Lilong Shi; Ilia Ovsiannikov; Dong-Ki Min; Yohwan Noh; Wanghyun Kim; Sunhwa Jung; Joonho Lee; Deokha Shin; Hyekyung Jung; Gregory Waligorski; Yibing Michelle Wang; Wendy Wang; Yoondong Park; Chilhee Chung

doi:10.1117/12.2001702

14 February 2013 Demosaicing for RGBZ sensor

Lilong Shi, Ilia Ovsiannikov, Dong-Ki Min, Yohwan Noh, Wanghyun Kim, Sunhwa Jung, Joonho Lee, Deokha Shin, Hyekyung Jung, Gregory Waligorski, Yibing Michelle Wang, Wendy Wang, Yoondong Park, Chilhee Chung

Author Affiliations +

Proceedings Volume 8657, Computational Imaging XI; 865705 (2013) https://doi.org/10.1117/12.2001702
Event: IS&T/SPIE Electronic Imaging, 2013, Burlingame, California, United States

Abstract

In this paper, we proposed a new technique for demosaicing a unique RGBZ color-depth imaging sensor, which captures color and depth images simultaneously, with a specially designed color-filter-array (CFA) where two out of six RGB color rows are replaced by “Z” pixels that capture depth information but no color information. Therefore, in an RGBZ image, the red, green and blue colors are more sparsely sampled than in a standard Bayer image. Due to the missing rows in the data image, commonly used demosaicing algorithms for the standard Bayer CFA cannot be applied directly. To this end, our method first fills-in the missing rows to reconstruct a full Bayer CFA, followed by a color-selective adaptive demosaicing algorithm that interpolates missing color components. In the first step, unlike common bilinear interpolation approaches that tend to blur edges, our edge-based directional interpolation approach, derived from de-interlacing techniques, emphasizes reconstructing more straight and sharp edges with fewer artifacts and thereby preserves the vertical resolution in the reconstructed the image. In the second step, to avoid using the newly estimated pixels for demosaicing, the bilateral-filter-based approach interpolates the missing color samples based on weighted average of adaptively selected known pixels from the local neighborhoods. Tests show that the proposed method reconstructs full color images while preserving edges details, avoiding artifacts, and removing noise with high efficiency.

Citation Download Citation

Lilong Shi, Ilia Ovsiannikov, Dong-Ki Min, Yohwan Noh, Wanghyun Kim, Sunhwa Jung, Joonho Lee, Deokha Shin, Hyekyung Jung, Gregory Waligorski, Yibing Michelle Wang, Wendy Wang, Yoondong Park, and Chilhee Chung "Demosaicing for RGBZ sensor", Proc. SPIE 8657, Computational Imaging XI, 865705 (14 February 2013); https://doi.org/10.1117/12.2001702

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available