19 August 2017 Low-light color image enhancement via iterative noise reduction using RGB/NIR sensor
Hiroki Yamashita, Daisuke Sugimura, Takayuki Hamamoto
Author Affiliations +
Abstract
We propose a method to enhance the color image of a low-light scene using a single sensor that simultaneously captures red, green, blue (RGB), and near-infrared (NIR) information. Typical image enhancement methods require two sensors to simultaneously capture color and NIR images. In contrast, our proposed system utilizes a single sensor but achieves accurate color image restoration. We divide the captured multispectral data into RGB and NIR information based on the spectral sensitivity of our imaging system. Using the NIR information for guidance, we reconstruct the corresponding color image based on a joint demosaicking and denoising technique. Subsequently, we restore the estimated color image iteratively using the constructed guidance image. Our experiments demonstrate the effectiveness of our method using synthetic data, and real raw data captured by our imaging system.
© 2017 SPIE and IS&T 1017-9909/2017/$25.00 © 2017 SPIE and IS&T
Hiroki Yamashita, Daisuke Sugimura, and Takayuki Hamamoto "Low-light color image enhancement via iterative noise reduction using RGB/NIR sensor," Journal of Electronic Imaging 26(4), 043017 (19 August 2017). https://doi.org/10.1117/1.JEI.26.4.043017
Received: 2 March 2017; Accepted: 18 July 2017; Published: 19 August 2017
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CITATIONS
Cited by 10 scholarly publications.
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KEYWORDS
Near infrared

RGB color model

Image enhancement

Sensors

Imaging systems

Denoising

Image processing

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