Journal of Systems Engineering and Electronics ›› 2022, Vol. 33 ›› Issue (2): 279-293.doi: 10.23919/JSEE.2022.000029

• ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

A single image dehazing method based on decomposition strategy

Chaoxuan QIN1,2(), Xiaohui GU1,*()   

  1. 1 School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
    1 Southwest Technology and Engineering Research Institute, Chongqing 400039, China
  • Received:2020-09-16 Accepted:2022-02-22 Online:2022-05-06 Published:2022-05-06
  • Contact: Xiaohui GU E-mail:qinchaoxuan1991@163.com;gxiaohui@njust.edu.cn
  • About author:|QIN Chaoxuan was born in 1991. He received his B.S. degree from the School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China, in 2014. He received his Ph.D. degree from the School of Mechanical Engineering, Nanjing University of Science and Technology, China, in 2021. He is currently working as an engineer with the Southwest Technology and Engineering Research Institute. His current research interests focus on computer vision, signal processing, and target identification. E-mail: qinchaoxuan1991@163.com||GU Xiaohui was born in 1964. He received his Ph.D. degree from the School of Mechanical Engineering, Nanjing University of Science and Technology, China in 2002. He is a professor and a doctoral supervisor at the School of Mechanical Engineering, Nanjing University of Science and Technology, China. His research interests include computer vision, artificial intelligence, and reliability engineering. E-mail: gxiaohui@njust.edu.cn
  • Supported by:
    This work was supported by the National Defense Technology Advance Research Project of China (004040204).

Abstract:

Outdoor haze has adverse impact on outdoor image quality, including contrast loss and poor visibility. In this paper, a novel dehazing algorithm based on the decomposition strategy is proposed. It combines the advantages of the two-dimensional variational mode decomposition (2DVMD) algorithm and dark channel prior. The original hazy image is adaptively decomposed into low-frequency and high-frequency images according to the image frequency band by using the 2DVMD algorithm. The low-frequency image is dehazed by using the improved dark channel prior, and then fused with the high-frequency image. Furthermore, we optimize the atmospheric light and transmittance estimation method to obtain a defogging effect with richer details and stronger contrast. The proposed algorithm is compared with the existing advanced algorithms. Experiment results show that the proposed algorithm has better performance in comparison with the state-of-the-art algorithms.

Key words: single image dehazing, decomposition strategy, image processing, global atmospheric light