Name
Title | ||
|---|---|---|
Graph-Based Transform with Weighted Self-Loops for Predictive Transform Coding Based on Template Matching |
Abstract | ||
|---|---|---|
This paper introduces the GBT-L, a novel class of Graph-based Transform within the context of block-based predictive transform coding. The GBT-L is constructed using a 2D graph with unit edge weights and weighted self-loops in every vertex. The weighted selfloops are selected based on the residual values to be transformed. To avoid signalling any additional information required to compute the inverse GBT-L, we also introduce a coding framework that uses a template-based strategy to predict residual blocks in the pixel and residual domains. Evaluation results on several video frames and medical images, in terms of the percentage of preserved energy and mean square error, show that the GBT-L can outperform the DST, DCT and the Graph-based Separable Transform. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/DCC.2019.00041 | 2019 Data Compression Conference (DCC) |
Keywords | Field | DocType |
Graph Based Transform, Weighted Self Loops, Graph Based Separable Transform, Predictive Transform Coding, Template Matching, Template Based Prediction, Prediction Inaccuracy Modeling, Compression, Video Coding | Template matching,Residual,Inverse,Computer vision,Computer science,Discrete cosine transform,Transform coding,Algorithm,Mean squared error,Coding (social sciences),Artificial intelligence,Pixel | Conference |
ISSN | ISBN | Citations |
1068-0314 | 978-1-7281-0658-8 | 1 |
PageRank | References | Authors |
0.37 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Debaleena Roy | 1 | 5 | 1.83 |
| Tanaya Guha | 2 | 4 | 3.83 |
| Victor Sanchez | 3 | 144 | 31.22 |