Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 384-389.doi: 10.11896/jsjkx.210400243

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Single Backlit Image Enhancement Based on Virtual Exposure Method

ZHAO Ming-hua1,2, ZHOU Tong-tong1, DU Shuang-li1, SHI Zheng-hao1   

  1. 1 School of Computer Science and Engineering,Xi'an University of Technology,Xi'an 710048,China
    2 Shaanxi Key Laboratory of Network Computing and Security Technology,Xi'an 710048,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:ZHAO Ming-hua,born in 1979,Ph.D,professor,is a senior member of China Computer Federation.Her main research interests include computer vision,and pattern recognition.
    DU Shuang-li,born in 1990,Ph.D,lecturer.Her main research interests include computer vision and so on.
  • Supported by:
    National Key R & D Program of China(2017YFB1402103-3),Key Laboratory Project of Shaanxi Provincial Department of Education(18JS078,20JS086),National Natural Science Foundation of China(61901363,61901362) and Natural Science Foundation of Shaanxi Province,China(2019JM-381,2019JQ-729).

Abstract: The visual quality of backlit image in target area is low and its background area is overexposed,which are important factors affecting image quality.Aiming at the problem that the existing backlit image enhancement methods cannot suppress the excessive enhancement of bright areas while enhancing the detail information of dark areas well,a single backlit image enhancement method based on virtual exposure is proposed in this paper.First,the virtual exposure image is introduced,and the best low-exposure image and high-exposure image are determined according to parameters.Then,the dark and bright areas are processed by nonlinear enhancement method and the neighborhood correlation method respectively.Finally,the details and features of the dark and bright areas are fused by Laplacian pyramid fusion method.Experiments results based on natural images and synthetic images show that the proposed method has less color and brightness distortion,and the visual effect is more natural.

Key words: Backlit image, Contrast enhancement, Image fusion, Nonlinear image enhancement, Virtual exposure method

CLC Number: 

  • TP391
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