{'fraction_non_alphanumeric': 0.02280501710376283, 'fraction_numerical': 0.0068415051311288486, 'mean_word_length': 5.36231884057971, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
No-reference PSNR estimation algorithm for H.264 encoded video sequences

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.