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A Parallel Retinex Image Enhancement Algorithm Based on OpenMP

  • Shixiong Cheng
  • Bin LiuEmail author
  • Dongjian He
  • Jinrong He
  • Yuancheng Li
  • Yanning Du
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11783)

Abstract

Retinex image enhancement algorithm occupies an important position in eliminating image uneven exposure, low contrast, and smog influence. However, with the increasing of image resolution, the real-time performance of the serial Retinex algorithm has not satisfied the requirements of practical applications. This paper proposes an OpenMP-based parallel Retinex algorithm. The parallelism of the Retinex algorithm is first identified by theoretical analyses. Then, the time-consuming sub-algorithms such as Gaussian convolution and exponential transformation, of the serial algorithm are designed and executed in parallel. On Tianhe-2 supercomputer platform, the experimental results show that the speedup of the parallel algorithm is significantly improved, and the test image set achieves an average speedup of 12. It indicates that the parallel algorithm can satisfy the needs of real-time processing in image enhancement field.

Keywords

Image enhancement Parallel algorithm Retinex OpenMP Agricultural image 

Notes

Acknowledgment

This research is supported by the National Natural Science Foundation of China under Grant No. 61602388, by the Natural Science Basic Research Plan in Shaanxi Province of China under Grant No. 2017JM6059, by the Fundamental Research Funds for the Central Universities 2452019064, by the China Postdoctoral Science Foundation under Grant No. 2017M613216, by the Postdoctoral Science Foundation of Shaanxi Province of China under Grant No. 2016BSHEDZZ121, by the Fundamental Research Funds for the Central Universities under Grants No. 2452016081, by the Key Program of the National Natural Science Foundation of China under Grant No. 61834005, by China Postdoctoral Science Foundation No. 2018M633585, by Natural Science Basic Research Plan in Shaanxi Province of China No. 2018JQ6060, by the Natural Science Basic Research Plan in Shaanxi Province of China under Grant No. 2015JM6355, and by Doctoral Starting up Foundation of Yan’an University YDBK2019-06.

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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Shixiong Cheng
    • 1
  • Bin Liu
    • 1
    • 2
    • 3
    Email author
  • Dongjian He
    • 2
    • 3
    • 4
  • Jinrong He
    • 5
  • Yuancheng Li
    • 6
  • Yanning Du
    • 7
  1. 1.College of Information EngineeringNorthwest A&F UniversityYanglingChina
  2. 2.Key Laboratory of Agricultural Internet of ThingsNorthwest A&F University, Ministry of Agriculture and Rural AffairsYanglingChina
  3. 3.Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent ServiceNorthwest A&F UniversityYanglingChina
  4. 4.College of Mechanical and Electronic EngineeringNorthwest A&F UniversityYanglingChina
  5. 5.College of Mathematics and Computer ScienceYan’an UniversityShaanxiChina
  6. 6.School of Computer Science and TechnologyXi’an University of Science and TechnologyXi’anChina
  7. 7.School of Computer Science and EngineeringXi’an University of TechnologyXi’anChina

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