Back to Search
Start Over
Variable Block-Sized Signal-Dependent Transform for Video Coding
- Source :
- IEEE Transactions on Circuits and Systems for Video Technology. 28:1920-1933
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- Transform, as one of the most important modules of mainstream video coding systems, seems very stable over the past several decades. However, recent developments indicate that bringing more options for transform can lead to coding efficiency benefits. In this paper, we go further to investigate how the coding efficiency can be improved over the state-of-the-art method by adapting a transform for each block. We present a variable block-sized signal-dependent transforms (SDTs) design based on the High Efficiency Video Coding (HEVC) framework. For a coding block ranged from $4\times4$ to $32\times32$ , we collect a quantity of similar blocks from the reconstructed area and use them to derive the Karhunen–Loeve transform. We avoid sending overhead bits to denote the transform by performing the same procedure at the decoder. In this way, the transform for every block is tailored according to its statistics, to be signal-dependent. To make the large block-sized SDTs feasible, we present a fast algorithm for transform derivation. Experimental results show the effectiveness of the SDTs for different block sizes, which leads to up to 23.3% bit-saving. On average, we achieve BD-rate saving of 2.2%, 2.4%, 3.3%, and 7.1% under AI-Main10, RA-Main10, RA-Main10, and LP-Main10 configurations, respectively, compared with the test model HM-12 of HEVC. The proposed scheme has also been adopted into the joint exploration test model for the exploration of potential future video coding standard.
- Subjects :
- Theoretical computer science
Macroblock
020206 networking & telecommunications
02 engineering and technology
Sub-band coding
Algorithmic efficiency
Sum of absolute transformed differences
0202 electrical engineering, electronic engineering, information engineering
Media Technology
Discrete cosine transform
Lapped transform
020201 artificial intelligence & image processing
Electrical and Electronic Engineering
Algorithm
Decoding methods
Transform coding
Mathematics
Subjects
Details
- ISSN :
- 15582205 and 10518215
- Volume :
- 28
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Circuits and Systems for Video Technology
- Accession number :
- edsair.doi...........9eb948794268ac9d84e22f9497b114e4