DocumentCode :
245526
Title :
Accelerating multi-scale retinex using ARM NEON
Author :
Ching-Tang Fan ; Jian-Ru Chen ; Chung-Wei Liang ; Yuan-Kai Wang
fYear :
2014
fDate :
26-28 May 2014
Firstpage :
77
Lastpage :
78
Abstract :
High dynamic range image processing have recently become an important topic in consumer electronics market. While multi-scale retinex with color restoration (MSRCR) have been well developed, disadvantages of low performance is not favorable to a mobile computer-vision system. To remedy the above problem, this paper proposes an accelerated MSRCR with effective use of ARM Cortex-A9 architecture and NEON SIMD technology. A linear sampling method with binomial normal approximation is developed for improving performance of Gaussian smoothing. Overall performance improvement of MSRCR algorithm on Zedboard platform is 74% compared to original ARM optimized C code compiled to Cortex-A9 processor architecture.
Keywords :
Gaussian processes; approximation theory; image colour analysis; image restoration; image sampling; microprocessor chips; smoothing methods; ARM Cortex-A9 processor architecture; ARM NEON; ARM optimized C code; Gaussian smoothing; MSRCR algorithm; NEON SIMD technology; Zedboard platform; binomial normal approximation; color restoration; consumer electronics market; high dynamic range image processing; linear sampling method; multiscale retinex acceleration; Acceleration; Approximation methods; Computer architecture; Image color analysis; Kernel; Lighting; Smoothing methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Consumer Electronics - Taiwan (ICCE-TW), 2014 IEEE International Conference on
Conference_Location :
Taipei
Type :
conf
DOI :
10.1109/ICCE-TW.2014.6904110
Filename :
6904110
Link To Document :
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