Orthogonal Directional Transforms Using Discrete Directional Laplacian Eigen Solutions for Beyond HEVC Intra Coding

Dvir, Itsik; Irony, Dror; Drezner, David; Ecker, Ady; Allouche, Amiram; Peterfreund, N.

doi:10.1109/tip.2020.2977863

Cited by 2 publications

(2 citation statements)

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“…The outstanding energy compaction and decorrelation capabilities of KLT attract researchers to study data-driven transform. Dvir et al [2] constructed a new transform from an eigen-decomposition of a discrete directional Laplacian system matrix. Lan et al [3] trained one dimensional KLT through searching patches similar with the current block from reconstructed frames with computational overhead.…”

Section: Introductionmentioning

confidence: 99%

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Explainable Machine Learning based Transform Coding for High Efficiency Intra Prediction

Li,

Zhang,

Kuo

2020

Preprint

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Machine learning techniques provide a chance to explore the coding performance potential of transform. In this work, we propose an explainable transform based intra video coding to improve the coding efficiency. Firstly, we model machine learning based transform design as an optimization problem of maximizing the energy compaction or decorrelation capability. The explainable machine learning based transform, i.e., Subspace Approximation with Adjusted Bias (Saab) transform, is analyzed and compared with the mainstream Discrete Cosine Transform (DCT) on their energy compaction and decorrelation capabilities. Secondly, we propose a Saab transform based intra video coding framework with off-line Saab transform learning. Meanwhile, intra mode dependent Saab transform is developed. Then, Rate-Distortion (RD) gain of Saab transform based intra video coding is theoretically and experimentally analyzed in detail. Finally, three strategies on integrating the Saab transform and DCT in intra video coding are developed to improve the coding efficiency. Experimental results demonstrate that the proposed 8×8 Saab transform based intra video coding can achieve Bjønteggard Delta Bit Rate (BDBR) from -1.19% to -10.00% and -3.07% on average as compared with the mainstream 8×8 DCT based coding scheme.

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Section: Introductionmentioning

confidence: 99%

“…MODE DEPENDENT SAAB TRANSFORM SET {SBT k } AND INTEGRATION STRATEGIES. Either DCT or SBT k is used depending on the intra mode 2. The optimal transform is selected from DCT and SBT k with RDO.…”

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confidence: 99%