Journal of Geo-information Science ›› 2019, Vol. 21 ›› Issue (4): 623-629.doi: 10.12082/dqxxkx.2019.180576

• Orginal Article • Previous Articles    

Implementation of Retinex Image Enhancement Algorithm on GPU Platform

Hao WANG1,2(), Hanyu WANG1,2,*(), Mingyu YANG1,2, Yongsen XU1,2   

  1. 1. Key Laboratory of Airborne Optical Imaging and Measurement, Chinese Academy of Sciences, Changchun 130033, China
    2. Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
  • Received:2018-11-13 Revised:2019-03-20 Online:2019-04-24 Published:2019-04-24
  • Contact: Hanyu WANG E-mail:wanghao7600@163.com;hanyu112@126.com
  • Supported by:
    The National Key Research and Development Program of China, No.2017YFB0503001, 2016YFC0803000

Abstract:

With the advent of the era of UAV,the real-time requriements for massive data processing are getting higher.Achieve parallel processing of Retinex image enhancement algorithm on the GPU (Graphic Processing Unit) platform, which improves the processing speed of Retinex image enhancement algorithm for processing high resolution digital images.Firstly, by data combine-accessing and memory data interaction technology realize fast access of data, shorten the transmission time of data between different kinds of memory, and improve the efficiency of data access. Then, using kernel instruction optimization and data parallel computing technology, the multi-core programming of Retinex image enhancement algorithm on GPU platform is realized.Finally, the asynchronous execution mode of the host and the device is used to perform parallel calculation of the kernel data while data transmission, and the execution time of the algorithm on the GPU platform is further shortened by the parallel of the task level. With the powerful parallel computing power of the GPU, the processing speed of the Retinex algorithm is greatly improved. For images of different resolutions, the processing speed of the Retinex image enhancement algorithm is tens of times higher than that of the CPU platform. Processing an image with a resolution of 2048×2048 pixels requires only 38.04 ms, and the processing speed of the algorithm is 40 times higher than that of the CPU.

Key words: GPU, image enhancement, Retinex algorithm, parallel computing, UAV