In lossy packet networks such as the Internet, information often gets lost due to, e.g., network congestion. While
these problems are typically solved by Active Error Concealment techniques such as error correcting codes,
they do not always work for applications such as real time video. In these cases, Passive Error Concealment is
essential. Passive error concealment exploits the redundancy in the video: lost data are estimated from their
correctly received neighboring data. In this paper, we focus on wavelet based video coding. We compress
video frames by dispersively spreading neighboring wavelet coefficients over different packets, and by coding
these packets independently from each other. If a packet gets lost during the transmission, we estimate the
missing data (wavelet coefficients in I-frames and P-frames, and motion vectors) with passive error concealment
In the proposed method, we extend our earlier image concealment method to video. This technique applies a
locally adaptive interpolation for the reconstruction of lost coefficients in the I-frames of wavelet coded video. We
also investigate how the lost coefficients in P-frames can be reconstructed. For the reconstruction of lost motion
vectors, we use the vector median filtering reconstruction technique. Compared to related video reconstruction
methods of similar complexity, the proposed scheme estimates the lost data much better. The reconstructed
video also looks better. As the proposed method is fast and of low complexity, it is widely usable.
In packet switched networks such as the Internet, packets may get lost during transmission due to, e.g., network
congestion. This leads to a quality degradation of the original signal. As video communication is a bandwidth
consuming application, the original data are first compressed. This compression step increases the impact of
information loss even more. In wavelet based image and video coding, the low frequency data is the most
important. Loss of low frequency coefficients results in annoying black holes in the received images and video.
This effect can be countered by post processing error concealment: a lost coefficient is estimated from its
In this paper we present a locally adaptive interpolation method for the lost low frequency coefficients. For
each lost low frequency coefficient, we estimate the optimal interpolation direction (horizontal or vertical) using
novel error measures. In this way, we preserve the edges in the reconstructed image much better. Compared to
older techniques of similar complexity, our scheme reconstructs images with the same or better quality. This is
reflected in the visual as well as in the numerical results: there is an increase of up to 4.4 dB compared to bilinear
concealment. The proposed scheme is fast and simple, which makes it suitable for real-time applications.
In this paper, we propose a passive error concealment scheme for the reconstruction of wavelet coded images which are damaged due to packet loss. The proposed interpolation scheme calculates a lost coefficient from its neighbors while adapting the interpolation weights to the image correlation in each direction. All subbands are processed independently which allows a fast, parallel execution. This is interesting for real-time video applications such as two way video communication. The results demonstrate that the proposed scheme outperforms the existing schemes of similar complexity, both in terms of mean squared error and visually.