A content-adaptive distortion-quantization model for H.264/AVC and its applications

Ching Yu Wu, Po Chyi Su

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Accurately estimating the resultant quality or distortion associated with quantization parameter (QP) is very helpful to video encoding. In this research, a content-adaptive distortion-quantization model for H.264/AVC is proposed to predict the distortion level, which is defined as the difference between the original video frame and the decoded one in the sum of squared errors. The proposed model has only one adjustable parameter related to the macroblock content and provides a mapping between QP and the corresponding distortion before the exact encoding process. Given a targeted frame quality measured in peak signal to noise ratio (PSNR), this model can help to assign a suitable QP value to each frame. Two applications are then presented, i.e., the single-pass constant frame PSNR coding and the two-pass coding with the additional bitrate or storage constraint, both of which may facilitate such applications of video archiving and editing. The experimental results show that the targeted PSNR of each decoded frame can be achieved effectively by the proposed mechanism.

Original languageEnglish
Article number6562767
Pages (from-to)113-126
Number of pages14
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume24
Issue number1
DOIs
StatePublished - Jan 2014

Keywords

  • Constant peak signal to noise ratio (PSNR)
  • H.264/AVC
  • distortion-quantization
  • quality control
  • rate control
  • sum of absolute transformed difference (SATD)

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