15 February 2017 SLMRACE: a noise-free RACE implementation with reduced computational time
Juliet Chauvin, Edoardo Provenzi
Author Affiliations +
Abstract
We present a faster and noise-free implementation of the RACE algorithm. RACE has mixed characteristics between the famous Retinex model of Land and McCann and the automatic color equalization (ACE) color-correction algorithm. The original random spray-based RACE implementation suffers from two main problems: its computational time and the presence of noise. Here, we will show that it is possible to adapt two techniques recently proposed by Banić et al. to the RACE framework in order to drastically decrease the computational time and noise generation. The implementation will be called smart-light-memory-RACE (SLMRACE).
© 2017 SPIE and IS&T 1017-9909/2016/$25.00 © 2016 SPIE and IS&T
Juliet Chauvin and Edoardo Provenzi "SLMRACE: a noise-free RACE implementation with reduced computational time," Journal of Electronic Imaging 26(3), 031202 (15 February 2017). https://doi.org/10.1117/1.JEI.26.3.031202
Received: 30 September 2016; Accepted: 6 December 2016; Published: 15 February 2017
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Colorimetry

Image filtering

Color vision

Convolution

Mirrors

RGB color model

Electronic imaging

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