Complex event classification in degraded image sequences

Rares, A.; Reinders, M.J.T.; Biemond, J.

doi:10.1109/icip.2001.959001

Cited by 11 publications

(12 citation statements)

References 4 publications

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“…In particular, the BTBR algorithms can remove the extremities of blotches very well, in comparison to the cut-and-paste operators used currently. Furthermore, because of the soft corruption model, we are able to bring more robustness to the PM problem without actually detecting PM explicitly [34][35][36][37]. Of course, a novel practical system would employ a PM detector with our BTBR to yield industrial strength performance.…”

Section: Resultsmentioning

confidence: 99%

“…Bornard [14] and Corrigan et al [34] pushed Roosmalen's ideas into a Bayesian framework, eventually incorporating MRF priors for blotch smoothness in time that allowed the blotch remover to implicitly disable itself when a blotch was being detected in more than one frame consecutively. Rares et al [35] used machine-learning-type ideas to detect picture material which was difficult for motion estimation, again turning off the process in difficult areas. http://jivp.eurasipjournals.com/content/2013/1/33…”

Section: Opaque Corruption Removalmentioning

confidence: 99%

“…This is a problem particularly with the movement of people and clothing. Bornard [14], Corrigan et al [34], Rares et al [35], Roosmalen [36], and Kent et al [37] introduced several mechanisms for dealing with such pathological motion effects. Roosmalen [36] concentrated on detecting failure in the motion estimator he used (based on phase correlation) by simply turning off the blotch remover when the displaced frame difference (DFD) was too high over many consecutive frames.…”

Section: Opaque Corruption Removalmentioning

confidence: 99%

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Blotch and scratch removal in archived film using a semi-transparent corruption model and a ground-truth generation technique

2013

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This paper has two main contributions. The first is a Bayesian framework for removing two common types of degradations on video known as blotches and line scratches. Most removal techniques assume complete obliteration of the original data at the corrupted sites. This often leads to the introduction of restoration artifacts during removal. Our framework is based on modeling corruption as a semi-transparent layer. This model was introduced earlier by Ahmed et al. (ICIP 2009) for the problem of blotch removal. We show much more blotch removal results than the previous work, and we extend the semi-transparent corruption model to the problem of line removal. The second contribution of this paper is an automated technique for ground-truth generation from infrared scans of corruptions. Previous ground-truth generation efforts require manually inpainting the corrupted regions. The restoration results are evaluated by comparing the reconstructed data against the ground-truth estimates. Comparisons with current blotch and line removal techniques show that the proposed corruption removal framework produces better removal and generates less restoration artifacts.

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Section: Resultsmentioning

confidence: 99%

Section: Opaque Corruption Removalmentioning

confidence: 99%

Section: Opaque Corruption Removalmentioning

confidence: 99%

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Blotch and scratch removal in archived film using a semi-transparent corruption model and a ground-truth generation technique

2013

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“…Useful information can be extracted about the type of motion that causes the failure of motion estimation [3], [6], and then used to further enhance the results of the current algorithm. These subjects will constitute the focus of our future research.…”

Section: Discussionmentioning

confidence: 99%

“…Instead of protecting the blotches from being restored [4], in our view, the detected artefacts should be restored based on spatial information alone [6], [7], discarding the temporal information. In the BRAVA project [8] of the European Union, we have devised a novel restoration algorithm that takes advantage of the available spatial information in order to restore the degraded film frames.…”

Section: Introductionmentioning

confidence: 99%

Edge-based image restoration

Rares

Reinders

Biemond

2005

IEEE Trans. on Image Process.

Self Cite

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Abstract-In this paper, we propose a new image inpainting algorithm that relies on explicit edge information. The edge information is used both for the reconstruction of a skeleton image structure in the missing areas, as well as for guiding the interpolation that follows. The structure reconstruction part exploits different properties of the edges, such as the colors of the objects they separate, an estimate of how well one edge continues into another one, and the spatial order of the edges with respect to each other. In order to preserve both sharp and smooth edges, the areas delimited by the recovered structure are interpolated independently, and the process is guided by the direction of the nearby edges. The novelty of our approach lies primarily in exploiting explicitly the constraint enforced by the numerical interpretation of the sequential order of edges, as well as in the pixel filling method which takes into account the proximity and direction of edges. Extensive experiments are carried out in order to validate and compare the algorithm both quantitatively and qualitatively. They show the advantages of our algorithm and its readily application to real world cases.

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Efficient detection of temporally impulsive dirt impairments in archived films

Ren

Vlachos

2007

Signal Processing

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Complex event classification in degraded image sequences

Cited by 11 publications

References 4 publications

Blotch and scratch removal in archived film using a semi-transparent corruption model and a ground-truth generation technique

Blotch and scratch removal in archived film using a semi-transparent corruption model and a ground-truth generation technique

Edge-based image restoration

Efficient detection of temporally impulsive dirt impairments in archived films

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