Laser & Optoelectronics Progress, Volume. 61, Issue 18, 1837004(2024)

Intelligent Optimization Algorithm for Codeword Searching for a Coded Exposure Camera

Peipei Zhou1, Jiayi Yan2, Huannan Qi1, Tao Sun2, and Xinglin Hou2、*
Author Affiliations
  • 1School of Electrical and Information Engineering, Changzhou Institute of Technology, Changzhou 213032, Jiangsu, China
  • 2School of Automotive Engineering, Changzhou Institute of Technology, Changzhou 213032, Jiangsu, China
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    Figures & Tables(8)
    Process of searching code word for coded exposure and recovering blurred image
    Schematics diagram of camera shutter switch in time and frequency domain. (a) Traditional camera shutter switch in time domain; (b) encodin camera shutter switch in time domain; (c) frequency spectrum of Fig.1(a); (d) frequency spectrum of Fig.2(b)
    Flow chart of the intelligent optimization algorithm
    Performance comparison curve of different code word acquisition methods
    Recovery results of flower with 32-bit codeword sequence. (a) Blurred image of code word exposure of reference [9] method; (b) blurred image of code word exposure of reference [4] method; (c) blurred image of code word exposure of proposed method; (d)‒(f) recovery results of image corresponding to Fig.5 (a)‒(c) respectively; (g)‒(i) local amplification maps corresponding to Fig.5 (d)‒(f) respectively
    Recovery results of figure with 32-bit codeword sequence. (a)‒(c) Exposure image with codeword of reference [9] and its recovery results; (d)‒(f) exposure image with codeword of reference [4] and their recovery results; (g)‒(i) exposure image with codeword of proposed method and recovery results
    Comparison results of different blurred images of shell exposed by different codeword sequences and the restoration images. (a) blurred image with the codeword of reference [9]; (b) blurred image with the codeword of reference [4]; (c) blurred image with the codeword of the proposed method; (d)‒(f) recovery results of image corresponding to Fig.7 (a)‒(c) respectively; (g)‒(i) local amplification maps corresponding to Fig.7 (d)‒(f) respectively
    • Table 1. Objective comparison of blurred image restoration results using different codeword acquisition methods

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      Table 1. Objective comparison of blurred image restoration results using different codeword acquisition methods

      MethodPSNR /dBSSIM
      flowerfigureshellflowerfigureshell
      Reference[930.1823.2828.390.960.860.93
      Reference[429.5222.6527.650.950.850.92
      Proposed method31.4623.3829.130.970.860.94
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    Peipei Zhou, Jiayi Yan, Huannan Qi, Tao Sun, Xinglin Hou. Intelligent Optimization Algorithm for Codeword Searching for a Coded Exposure Camera[J]. Laser & Optoelectronics Progress, 2024, 61(18): 1837004

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    Paper Information

    Category: Digital Image Processing

    Received: Dec. 11, 2023

    Accepted: Jan. 30, 2024

    Published Online: Sep. 14, 2024

    The Author Email: Xinglin Hou (houxl@czust.edu.cn)

    DOI:10.3788/LOP232651

    CSTR:32186.14.LOP232651

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