Texture aware image error concealment

@article{Uhlikova2015TextureAI,
  title={Texture aware image error concealment},
  author={Ivana Uhlikova and Wanda Benesova and Jaroslav Polec and Tibor Cs{\'o}ka},
  journal={IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON)},
  year={2015},
  pages={1-6}
}
Error concealment is an error control technique capable of mitigating the error effects on multimedia using only the correctly received data. We introduce an efficient and highly scalable concealment algorithm for textured colour images. The lost area is restored by texture extrapolation from the surrounding regions logically associated on the superpixel level. With the proposed method also edges located in the lost area are retained. We validate results of the experiments against state of the… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-2 OF 2 CITATIONS

Texture aware image error concealment with fuzzy segmentation

  • 2016 International Conference on Systems, Signals and Image Processing (IWSSIP)
  • 2016
VIEW 6 EXCERPTS
CITES METHODS

Superpixels merging in corrupted color images

  • 2017 Signal Processing Symposium (SPSympo)
  • 2017
VIEW 1 EXCERPT
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-10 OF 30 REFERENCES

Group-Based Sparse Representation for Image Restoration

  • IEEE Transactions on Image Processing
  • 2014
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Lossless true color image suite

Kodak
  • http://r0k.us/graphics/kodak/, accessed June 2015.
  • 2015
VIEW 1 EXCERPT

Frequency selective extrapolation with residual filtering for image error concealment

  • 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2014
VIEW 2 EXCERPTS

Robust object tracking via sparsity-based collaborative model

  • 2012 IEEE Conference on Computer Vision and Pattern Recognition
  • 2012
VIEW 1 EXCERPT

SLIC Superpixels Compared to State-of-the-Art Superpixel Methods

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2012
VIEW 3 EXCERPTS