Volume 46 Issue 7
Aug.  2017
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Hou Xinglin, Luo Haibo, Zhou Peipei. Multi-exposure control method based on maximum local information entropy[J]. Infrared and Laser Engineering, 2017, 46(7): 726001-0726001(7). doi: 10.3788/IRLA201746.0726001
Citation: Hou Xinglin, Luo Haibo, Zhou Peipei. Multi-exposure control method based on maximum local information entropy[J]. Infrared and Laser Engineering, 2017, 46(7): 726001-0726001(7). doi: 10.3788/IRLA201746.0726001

Multi-exposure control method based on maximum local information entropy

doi: 10.3788/IRLA201746.0726001
  • Received Date: 2016-11-11
  • Rev Recd Date: 2016-12-03
  • Publish Date: 2017-07-25
  • In the process of obtaining high dynamic range(HDR) image using the fusion of multiple shot images, the selection of exposure time in traditional method is blind, which makes the image information redundant and thus affects the fusion efficiency. In this paper, a method of multi-exposure control based on maximum local information entropy was proposed. The relationship between information entropy and exposure time of low dynamic scene was discussed. It was concluded that the image information entropy of a low dynamic range scene increased first and then decreased with the increase of exposure time. And information entropy achieved the maximum at a certain exposure time. For a high dynamic range scene, firstly, the range of exposure time was determined by using the approximate linear relationship between the gray level of the image and the exposure time. Secondly, the high dynamic range scene was divided into several low dynamic range(LDR) regions by using the histogram of the image. At last, the optimal exposure time of each region was searched. The method combined the local information entropy with the exposure time, which maked different exposure to different regions and avoided the shortcomings of the traditional exposure control effectively. Experimental results show that the image obtained with the proposed method has a good effect.
  • [1] Chaurasiya R K, Ramakrishnan K. High dynamic range imaging[C]//Proceedings of Communication Systems and Network Technologies(CSNT), 2013 International Conference on, IEEE, 2013:83-89.
    [2] Lv Weizheng, Liu Weiqi, Wei Zhonglun, et al. Design of high dynamic range imaging optical system based on DMD[J]. Infrared and Laser Engineering, 2014, 43(4):1167-1171. (in Chinese)
    [3] An Ran, Chen Yan, Xie Jing. Exposure algorithm for CMOS image sensor with adaptive dynamic range[J]. Infrared and Laser Engineering, 2013, 42(S1):89-92. (in Chinese)
    [4] Hou Xinglin, Luo Haibo, Zhou Peipei, et al. HDR imaging based on region segmentation[C]//Proceedings of Control and Decision Conference(CCDC), 2015:1111-1116.
    [5] Shen R, Cheng I, Shi J, et al. Generalized random walks for fusion of multi-exposure images[J]. Image Processing, IEEE Transactions on, 2011, 20(12):3634-3646.
    [6] Piao Y, Xu W. Method of auto multi-exposure for high dynamic range imaging[C]//Proceedings of Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on, IEEE, 2010:93-97.
    [7] Vuong Q K, Yun S H, Kim S. A new auto exposure system to detect high dynamic range conditions using CMOS technology[C]//Proceedings of Convergence and Hybrid Information Technology, 2008. ICCIT'08. Third International Conference on, IEEE, 2008:577-580.
    [8] Pourreza-Shahri R, Kehtarnavaz N. Automatic exposure selection for high dynamic range photography[C]//Proceedings of Consumer Electronics (ICCE), 2015 IEEE International Conference on, IEEE, 2015:471-472.
    [9] Huang K F, Chiang J C. Intelligent exposure determination for high quality HDR image generation[C]//Proceedings of Image Processing (ICIP), 201320th IEEE International Conference on, IEEE, 2013:3201-3205.
    [10] Hirakawa K, Wolfe P J. Optimal exposure control for high dynamic range imaging[C]//Proceedings of Image Processing (ICIP), 201017th IEEE International Conference on, IEEE, 2010:3137-3140.
    [11] Vallikumari V, RaviKiran B, Raju K. HDR scene detection and capturing strategy[C]//Proceedings of 2011 Annual IEEE India Conference on, IEEE, 2011:10.1109/INDCON.2011.6139400.
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Multi-exposure control method based on maximum local information entropy

doi: 10.3788/IRLA201746.0726001
  • 1. Shenyang Institute of Automation,Chinese Academy of Sciences,Shenyang 110016,China;
  • 2. University of Chinese Academy of Sciences,Beijing 100049,China;
  • 3. Key Laboratory of Opt-Electronic Information Processing,Chinese Academy of Sciences,Shenyang 110016,China;
  • 4. Key Laboratory of Image Understanding and Computer Vision,Shenyang 110016,China

Abstract: In the process of obtaining high dynamic range(HDR) image using the fusion of multiple shot images, the selection of exposure time in traditional method is blind, which makes the image information redundant and thus affects the fusion efficiency. In this paper, a method of multi-exposure control based on maximum local information entropy was proposed. The relationship between information entropy and exposure time of low dynamic scene was discussed. It was concluded that the image information entropy of a low dynamic range scene increased first and then decreased with the increase of exposure time. And information entropy achieved the maximum at a certain exposure time. For a high dynamic range scene, firstly, the range of exposure time was determined by using the approximate linear relationship between the gray level of the image and the exposure time. Secondly, the high dynamic range scene was divided into several low dynamic range(LDR) regions by using the histogram of the image. At last, the optimal exposure time of each region was searched. The method combined the local information entropy with the exposure time, which maked different exposure to different regions and avoided the shortcomings of the traditional exposure control effectively. Experimental results show that the image obtained with the proposed method has a good effect.

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