Shearlet-based Inverse Halftoning

نویسندگان

  • CHENGZHI DENG
  • WEI TIAN
  • SAIFENG HU
  • YAN LI
چکیده

Under the linear approximation model for error diffusion halftoning, a shearlet-based inverse halftoning (SIH) algorithm is proposed. The SIH algorithm performs inverse halftoning by first inverting the modelspecified convolution operator and then reducing the residual color noise using scalar shearlet-domain thresholding. The optimal thresholds are derived by using the maximum a posteriori rule. Experimental results demonstrate that SIH algorithm is competitive with state-of-the-art classical inverse techniques in peak signal-to-noise ratio (PSNR) sense. And the SIH algorithm also provides good visual quality.

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تاریخ انتشار 2013