Enhancing the error detection capabilities of DCT based codecs using compressed domain dissimilarity metrics

Abstract

Video compression standards are implemented in wireless data transmission technologies to provide multimedia services efficiently. These compression standards generally utilize the Discrete Cosine Transform (DCT) in conjunction with variable length codes (VLC) in order to achieve the required high compression ratios. While providing the necessary high data rates, this technique has the disadvantage of making the system more susceptible to transmission errors. The standard decoders do not manage to detect a large number of corrupted macroblocks, 40.54% not detected for H.263+, contributing to a significant reduction in the end-to-end video quality as perceived by the end-user. This paper presents three dissimilarity metrics which contain both color and texture information and that can be extracted directly from the compressed DCT coefficients. These metrics can be used to enhance the error-detection capabilities of standard DCT based codecs. Simulation results show that the proposed algorithm increases the error detection rate by 54.06% with a gain in peak signal-to-noise ratio (PSNR) of 3.21 dB. This improvement in performance is superior to other solutions found in literature.