A kernel-based statistical analysis of the residual error in video coding

Santiago De-Luxan-Hernandez, Detlev Marpe, Klaus Muller, Thomas Wiegand

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Video compression techniques exploit the statistical redundancy present in video signals to efficiently reduce the amount of information sent to the decoder. We contribute with a kernel-based analysis of the residual error blocks. In particular, we borrow dimension reduction techniques from machine learning, namely Principal Component Analysis (PCA) and nonlinear Kernel Principal Component Analysis (KPCA), to assess the spatial structure of block residuals. Interestingly, a nonlinear structure is observed that correlates to the rate-distortion costs of the blocks. Simulations by using a test set of videos with cropped Ultra High Definition (UHD) resolution show interesting results.

Original languageEnglish
Title of host publication2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages192-195
Number of pages4
ISBN (Print)9781467383530
DOIs
Publication statusPublished - 2015 Oct 30
Externally publishedYes
Event22nd International Conference on Systems, Signals and Image Processing, IWSSIP 2015 - London, United Kingdom
Duration: 2015 Sep 102015 Sep 12

Other

Other22nd International Conference on Systems, Signals and Image Processing, IWSSIP 2015
CountryUnited Kingdom
CityLondon
Period15/9/1015/9/12

Fingerprint

Image coding
Principal component analysis
Statistical methods
Image compression
Redundancy
Learning systems
Costs

Keywords

  • KPCA
  • PCA
  • Rate-Distortion Cost
  • Residual Error Coding

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

De-Luxan-Hernandez, S., Marpe, D., Muller, K., & Wiegand, T. (2015). A kernel-based statistical analysis of the residual error in video coding. In 2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015 (pp. 192-195). [7314209] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWSSIP.2015.7314209

A kernel-based statistical analysis of the residual error in video coding. / De-Luxan-Hernandez, Santiago; Marpe, Detlev; Muller, Klaus; Wiegand, Thomas.

2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 192-195 7314209.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

De-Luxan-Hernandez, S, Marpe, D, Muller, K & Wiegand, T 2015, A kernel-based statistical analysis of the residual error in video coding. in 2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015., 7314209, Institute of Electrical and Electronics Engineers Inc., pp. 192-195, 22nd International Conference on Systems, Signals and Image Processing, IWSSIP 2015, London, United Kingdom, 15/9/10. https://doi.org/10.1109/IWSSIP.2015.7314209
De-Luxan-Hernandez S, Marpe D, Muller K, Wiegand T. A kernel-based statistical analysis of the residual error in video coding. In 2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 192-195. 7314209 https://doi.org/10.1109/IWSSIP.2015.7314209
De-Luxan-Hernandez, Santiago ; Marpe, Detlev ; Muller, Klaus ; Wiegand, Thomas. / A kernel-based statistical analysis of the residual error in video coding. 2015 22nd International Conference on Systems, Signals and Image Processing - Proceedings of IWSSIP 2015. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 192-195
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