Edge‐based spatial concealment of digital dropout error in degraded archived media

Abstract

A spatial concealment technique, based on the concept of the strength of an edge, is proposed for 'digital dropout' error, evident in old archived media. As long as the presence of pathological motion is observed in video sequences where current state-of-the-art methods fail to reproduce correct information, such spatial restoration offers a much better solution in terms of quality and complexity. Furthermore, relevant edge-based weighted interpolation is able to restore complicated edges and complex textures from the available neighbourhood. An experiment is performed on real video archives to evaluate the efficacy of the proposed technique.Introduction: Digital dropout is a major type of damage when storing digital AV content on digital video tape carriers or when transferring this content to file-based environments. Dropouts are caused by momentary loss of tape contact with the playback head or by flaws on the tape or other features that cause an increase in the head-to-tape spacing. The digital dropout errors in archived videos tend to occur in blocks (size of 8 × 8) with significant patterns as described in Fig. 1. Despite the practical importance of algorithms for the concealment of dropouts originating from digital video tapes (Digi Beta, IMX etc.), there is only very little related scientific work focusing on image-based methods focusing on this kind of defect. The closest related work is given by Kokaram [1] in which the Bayesian approach computes the required information from the current and surrounding frames. Kokaram also assumed that corruption does not occur at the same location in consecutive frames, however this is not always the case. Another limitation of this spatio-temporal model is that, in the presence of pathological motion (PM), motion estimation will fail, i.e. in some parts of any sequence it will be impossible to model the behaviour. So, coping with PM remains an unsolved issue for this approach.

Frame Interpolation for Cloud-Based Mobile Video Streaming

“…This approach works well with sufficient information from nearby edges but does not produce better results in heavy losses. The relevant edges in the presence of digital drop out errors are estimated through canny edge detector [20]. This approach produces better results in linear motion only.…”

Survey of Error Concealment techniques: Research directions and open issues

“…This approach produces a defined number of computations, and is suitable for images having significant edges with details. The Canny edge detector is used to detect relevant edges in order to conceal digital dropout errors for the content of digital video tapes in [11]. This technique can restore complex edges and non-linear features with controlled computational complexity.…”

“…This approach can reconstruct complex textures, but is computationally complex and requires accelerated hardware. The approaches presented in [10][11][12] produce a better reconstruction performance with simple operations and are suitable for the random loss of data.…”

Structural pattern‐based approach for Betacam dropout detection in degraded archived media

“…Moreover, Kokaram's system often falls short in responding to the errors occurring in consecutive frames at the same position. It also shows shortcomings in detecting some other major errors, such as blotches, digital dropout, Betacam dropout, blockiness etc., as discussed in [8–13].…”