# Efficient Multiple Line-Based Intra Prediction for HEVC

arXiv: https://arxiv.org/abs/1605.08308 · HTML: https://mlsanity.com/paper/1605.08308/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 26 May 2016.

## Built on by (most cited first, 4 of 4)

- [Interactive Face Video Coding: A Generative Compression Framework](https://mlsanity.com/paper/2302.09919/) (2023)
- [Semantically Video Coding: Instill Static-Dynamic Clues into Structured Bitstream for AI Tasks](https://mlsanity.com/paper/2201.10162/) (2022)
- [Deep Learning-Based Intra Mode Derivation for Versatile Video Coding](https://mlsanity.com/paper/2204.04059/) (2022)
- [Coding for Intelligence from the Perspective of Category](https://mlsanity.com/paper/2407.01017/) (2024)

## Abstract (arXiv)

Traditional intra prediction usually utilizes the nearest reference line to generate the predicted block when considering strong spatial correlation. However, this kind of single line-based method does not always work well due to at least two issues. One is the incoherence caused by the signal noise or the texture of other object, where this texture deviates from the inherent texture of the current block. The other reason is that the nearest reference line usually has worse reconstruction quality in block-based video coding. Due to these two issues, this paper proposes an efficient multiple line-based intra prediction scheme to improve coding efficiency. Besides the nearest reference line, further reference lines are also utilized. The further reference lines with relatively higher quality can provide potential better prediction. At the same time, the residue compensation is introduced to calibrate the prediction of boundary regions in a block when we utilize further reference lines. To speed up the encoding process, this paper designs several fast algorithms. Experimental results show that, compared with HM-16.9, the proposed fast search method achieves 2.0% bit saving on average and up to 3.7%, with increasing the encoding time by 112%.