Title :
No-reference PSNR estimation algorithm for H.264 encoded video sequences
Author :
Brandao, Tomas ; Queluz, Maria Paula
Author_Institution :
Dept. of Sci. & Inf. Technol., Univ. Inst. of Lisbon, Lisbon, Portugal
Abstract :
This paper proposes a no-reference PSNR estimation algorithm for video sequences subject to H.264/AVC encoding. The proposed method explores statistical properties of the transformed coefficients, which can be modeled by a Cauchy or Laplace probability density function. The distribution´s parameters are computed from quantized coefficient data received at the decoder, combining maximum-likelihood with linear prediction estimates. Since the proposed algorithm has no knowledge about the original sequences, it can be used as a no-reference metric for evaluating the quality of the encoded video sequences. When compared with recent state-of-the-art algorithms proposed for the same purpose, it has shown better PSNR estimation accuracy in a set of video sequences subject to different encoding rates.
Keywords :
maximum likelihood estimation; probability; video coding; H.264 encoded video sequences; linear prediction estimates; maximum-likelihood estimation; no-reference PSNR estimation algorithm; probability density function; quantized coefficient data; transformed coefficients; Discrete cosine transforms; Encoding; Maximum likelihood estimation; PSNR; Signal processing algorithms; Video sequences;
Conference_Titel :
Signal Processing Conference, 2008 16th European
Conference_Location :
Lausanne