No reference PSNR estimation for compressed pictures

Deepak S. Turaga, Yingwei Chen, Jorge Caviedes

Research output: Contribution to journalArticlepeer-review

114 Scopus citations

Abstract

Many user-end applications require an estimate of the quality of coded video or images without having access to the original, i.e. a no-reference quality metric. Furthermore, in many such applications the compressed video bitstream is also not available. This paper describes methods for using the statistical properties of intra coded video data to estimate the quantization error caused by compression without accessing either the original pictures or the bitstream. We derive closed form expressions for the quantization error in coding schemes based on the discrete cosine transform and block based coding. A commonly used quality metric, the peak signal to noise ratio (PSNR) is subsequently computed from the estimated quantization error. Since quantization error is the most significant loss incurred during typical coding schemes, the estimated PSNR, or any PSNR-based quality metric may be used to gauge the overall quality of the pictures.

Original languageEnglish (US)
Pages (from-to)173-184
Number of pages12
JournalSignal Processing: Image Communication
Volume19
Issue number2
DOIs
StatePublished - Feb 2004
Externally publishedYes

Keywords

  • No-reference quality measurement
  • PSNR estimation

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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