• DocumentCode
    248302
  • Title

    High bit-precision image acquisition and reconstruction by planned sensor distortion

  • Author

    Pengfei Wan ; Au, Oscar C. ; Jiahao Pang ; Ketan Tang ; Rui Ma

  • Author_Institution
    Hong Kong Univ. of Sci. & Technol., Hong Kong, China
  • fYear
    2014
  • fDate
    27-30 Oct. 2014
  • Firstpage
    1773
  • Lastpage
    1777
  • Abstract
    We present a novel framework for high bit-precision image acquisition and reconstruction. This framework is designed based on the inherent Markov property of image signals. In acquisition stage, we add planned sensor distortion (PSD) to the analog image signal before feeding it to A/D converters (or quantizers) in camera sensor. In reconstruction stage, the acquired quantized pixel values are jointly combined to get the reconstructed signal with reduced uncertainty range. Advantages of proposed PSD framework include 1) simplicity: it does not require any change to the core hardware of existing A/D converters; 2) effectiveness: experiment results demonstrate significant PSNR gain over traditional methods (up to 10 dB when quantizer bit-depth is relatively low); and 3) generality: this framework can also be applied for acquisition of other analog signals, including audio, video, etc.
  • Keywords
    Markov processes; image reconstruction; image sensors; quantisation (signal); A/D converter; Markov property; PSD framework; PSNR gain; analog image signal; analog signal; camera sensor; high bit-precision image acquisition; image reconstruction; planned sensor distortion; quantized pixel value; quantizer bit-depth; reconstructed signal; reconstruction stage; Gain; Image reconstruction; Joints; Nickel; PSNR; Quantization (signal); Uncertainty; Bit-depth enhancement; image acquisition; inverse quantization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2014 IEEE International Conference on
  • Conference_Location
    Paris
  • Type

    conf

  • DOI
    10.1109/ICIP.2014.7025355
  • Filename
    7025355