The Korea Institute of Information and Commucation Engineering 2010; 8(3): 323-327
Published online June 30, 2010
https://doi.org/10.6109/jicce.2010.8.3.323
© Korea Institute of Information and Communication Engineering
Recently, the television market trend is change to HD television and the need of the study on HD image enhancement is increased rapidly. To enhancement of image quality, the retinex algorithm is commonly used. That's why we studied how to accelerate the retinex algorithm with CUDA on GPGPU (general purpose graphics processing unit). Calculating average part in retinex algorithm is similar to pyramidal calculation. We parallelize this recursive pyramidal average calculating for all layers, map the average data into the 2D plane and reduce the calculating time dramatically. Sequential C code takes 8948ms to get the average values for all layers in
Keywords CUDA,GPGPU,Image enhancement,Pyramidal calculation,Retinex
The Korea Institute of Information and Commucation Engineering 2010; 8(3): 323-327
Published online June 30, 2010 https://doi.org/10.6109/jicce.2010.8.3.323
Copyright © Korea Institute of Information and Communication Engineering.
Seo, Hyo-Seok;Kwon, Oh-Young;
Department of electrical and electronic engineering, Korea University of Technology and Education, School of Computer Science and Engineering, Korea University of Technology and Education
Recently, the television market trend is change to HD television and the need of the study on HD image enhancement is increased rapidly. To enhancement of image quality, the retinex algorithm is commonly used. That's why we studied how to accelerate the retinex algorithm with CUDA on GPGPU (general purpose graphics processing unit). Calculating average part in retinex algorithm is similar to pyramidal calculation. We parallelize this recursive pyramidal average calculating for all layers, map the average data into the 2D plane and reduce the calculating time dramatically. Sequential C code takes 8948ms to get the average values for all layers in
Keywords: CUDA,GPGPU,Image enhancement,Pyramidal calculation,Retinex