Lifting Transforms on Graphs for Video Coding

Martinez-Enriquez, Eduardo; Ortega, Antonio

doi:10.1109/dcc.2011.15

Cited by 16 publications

(24 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to obtain an improved complete encoder, we propose a reordering method and a new entropy coder, significantl improving previous versions of the encoder. Finally, we extend the results in [33]- [35] by including a comparison of the proposed encoder with MCTF and H.264/AVC video encoders for QCIF and CIF sequences.…”

Section: Contributionsmentioning

confidence: 99%

“…Previous work was presented by the authors in [33]- [35]. In this paper we formalize and solve analytically some of the underlying problems that arise from the transform design, describing and optimizing the complete scheme.…”

Section: Contributionsmentioning

confidence: 99%

“…It can be proven [45] that, considering that v ηm = v η and that v ǫm = v ǫ for any m ∈ V, the prediction error of i is given by…”

Section: U /P Assignmentmentioning

confidence: 99%

“…1) Coloring-based U /P Assignment: As we proposed in [33], [34], one good solution to address the U /P assignment is by solving the WMC problem. The underlying idea is to maximize the reliability with which update nodes can predict prediction neighbors, which intuitively seems equivalent to maximize the total weight of the links between the P and U sets.…”

Section: U /P Assignmentmentioning

confidence: 99%

See 3 more Smart Citations

Directional Transforms for Video Coding Based on Lifting on Graphs

Martinez-Enriquez

Cid-Sueiro

Díaz-de-María

et al. 2018

IEEE Trans. Circuits Syst. Video Technol.

Self Cite

View full text Add to dashboard Cite

Abstract-In this work we describe and optimize a general scheme based on lifting transforms on graphs for video coding. A graph is constructed to represent the video signal. Each pixel becomes a node in the graph and links between nodes represent similarity between them. Therefore, spatial neighbors and temporal motion-related pixels can be linked, while nonsimilar pixels (e.g., pixels across an edge) may not be. Then, a lifting-based transform, in which filterin operations are performed using linked nodes, is applied to this graph, leading to a 3-dimensional (spatio-temporal) directional transform which can be viewed as an extension of wavelet transforms for video. The design of the proposed scheme requires four main steps: (i) graph construction, (ii) graph splitting, (iii) filte design, and (iv) extension of the transform to different levels of decomposition. We focus on the optimization of these steps in order to obtain an effective transform for video coding. Furthermore, based on this scheme, we propose a coefficien reordering method and an entropy coder leading to a complete video encoder that achieves better coding performance than a motion compensated temporal filterin wavelet-based encoder and a simple encoder derived from H.264/AVC that makes use of similar tools as our proposed encoder (reference software JM15.1 configu ed to use 1 reference frame, no subpixel motion estimation, 16 × 16 inter and 4 × 4 intra modes).

show abstract

Section: Contributionsmentioning

confidence: 99%

Section: Contributionsmentioning

confidence: 99%

“…It can be proven [45] that, considering that v ηm = v η and that v ǫm = v ǫ for any m ∈ V, the prediction error of i is given by…”

Section: U /P Assignmentmentioning

confidence: 99%

Section: U /P Assignmentmentioning

confidence: 99%

See 2 more Smart Citations

Directional Transforms for Video Coding Based on Lifting on Graphs

Martinez-Enriquez

Cid-Sueiro

Díaz-de-María

et al. 2018

IEEE Trans. Circuits Syst. Video Technol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In the present study we will focus on lifting over graphs [8] which has been explored in other domains and successfully applied to video compression [23].…”

mentioning

confidence: 99%

Multiresolution analysis over simple graphs for brain computer interfaces

2013

View full text Add to dashboard Cite

Abstract. Objective: Multiresolution analysis (MRA) offers a useful framework for signal analysis in the temporal and spectral domains, although commonly employed MRA methods such as Daubechies wavelets may not be the best approach for brain computer interface (BCI) applications. Approach: Hereby we propose the use of a lifting scheme transform over graphs and a tailored simple graph representation for EEG data which results on a MRA system where temporal, spectral and spatial characteristics are used to extract motor imagery features. The transformed data is processed within a simple experimental framework to test the classification performance. Main Results: The proposed method can significantly improve the classification results obtained by various wavelet families using the same methodology. Preliminary results using common spatial patterns as feature extraction method show that we can achieve comparable classification accuracy to more sophisticated methodologies. From the analysis of the results we can obtain insights into the pattern development in the EEG data, which provide useful information for feature basis selection and thus for improving classification performance. Significance: Applying wavelet lifting over graphs is a new approach for handling BCI data. The inherent flexibility of the lifting scheme could lead to new approaches based on the proposed method which could further improve the classification performance here presented.

show abstract

Graph Spectral Image Processing

Cheung

Magli

Tanaka

et al. 2021

View full text Add to dashboard Cite

Lifting Transforms on Graphs for Video Coding

Cited by 16 publications

References 13 publications

Directional Transforms for Video Coding Based on Lifting on Graphs

Directional Transforms for Video Coding Based on Lifting on Graphs

Multiresolution analysis over simple graphs for brain computer interfaces

Graph Spectral Image Processing

Contact Info

Product

Resources

About