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Open AccessArticle

Adaptive Image Rendering Using a Nonlinear Mapping-Function-Based Retinex Model

School of Electronic Engineering, Soongsil University, Seoul 06978, Korea
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Author to whom correspondence should be addressed.
Sensors 2019, 19(4), 969; https://doi.org/10.3390/s19040969
Received: 12 February 2019 / Accepted: 21 February 2019 / Published: 25 February 2019
(This article belongs to the Special Issue Computational Intelligence-Based Sensors)
This paper introduces an adaptive image rendering using a parametric nonlinear mapping-function-based on the retinex model in a low-light source. For this study, only a luminance channel was used to estimate the reflectance component of an observed low-light image, therefore halo artifacts coming from the use of the multiple center/surround Gaussian filters were reduced. A new nonlinear mapping function that incorporates the statistics of the luminance and the estimated reflectance in the reconstruction process is proposed. In addition, a new method to determine the gain and offset of the mapping function is addressed to adaptively control the contrast ratio. Finally, the relationship between the estimated luminance and the reconstructed luminance is used to reconstruct the chrominance channels. The experimental results demonstrate that the proposed method leads to the promised subjective and objective improvements over state-of-the-art, scale-based retinex methods. View Full-Text
Keywords: image rendering; nonlinear mapping function; retinex model; statistics; contrast ratio image rendering; nonlinear mapping function; retinex model; statistics; contrast ratio
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Oh, J.; Hong, M.-C. Adaptive Image Rendering Using a Nonlinear Mapping-Function-Based Retinex Model. Sensors 2019, 19, 969.

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