• Title/Summary/Keyword: dequantization, quantization error

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Inverse quantization of DCT coefficients using Laplacian pdf (Laplacian pdf를 적용한 DCT 계수의 역양자화)

  • 강소연;이병욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.6C
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    • pp.857-864
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    • 2004
  • Many image compression standards such as JPEG, MPEG or H.263 are based on the discrete cosine transform (DCT) and quantization method. Quantization error. is the major source of image quality degradation. The current dequantization method assumes the uniform distribution of the DCT coefficients. Therefore the dequantization value is the center of each quantization interval. However DCT coefficients are regarded to follow Laplacian probability density function (pdf). The center value of each interval is not optimal in reducing squared error. We use mean of the quantization interval assuming Laplacian pdf, and show the effect of correction on image quality. Also, we compare existing quantization error to corrected quantization error in closed form. The effect of PSNR improvements due to the compensation to the real image is in the range of 0.2 ∼0.4 ㏈. The maximum correction value is 1.66 ㏈.

Applications of Regularized Dequantizers for Compressed Images (압축된 영상에서 정규화 된 역양자화기의 응용)

  • Lee, Gun-Ho;Sung, Ju-Seung;Song, Moon-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.39 no.5
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    • pp.11-20
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    • 2002
  • Based on regularization principles, we propose a new dequantization scheme on DCT-based transform coding for reducing of blocking artifacts and minimizing the quantization error. The conventional image dequantization is simply to multiply the received quantized DCT coefficients by the quantization matrix. Therefore, for each DCT coefficients, we premise that the quantization noise is as large as half quantizer step size (in DCT domain). Our approach is based on basic constraint that quantization error is bounded to ${\pm}$(quantizer spacing/2) and at least there are not high frequency components corresponding to discontinuities across block boundaries of the images. Through regularization, our proposed dequantization scheme, sharply reduces blocking artifacts in decoded images. Our proposed algorithm guarantees that the dequantization process will map the quantized DCT coefficients will be evaluated against the standard JPEG, MPEG-1 and H.263 (with Annex J deblocking filter) decoding process. The experimental results will show visual improvements as well as numerical improvements in terms of the peak-signal-to-noise ratio (PSNR) and the blockiness measure (BM) to be defined.