41,464 research outputs found
Lossless Intra Coding in HEVC with 3-tap Filters
This paper presents a pixel-by-pixel spatial prediction method for lossless
intra coding within High Efficiency Video Coding (HEVC). A well-known previous
pixel-by-pixel spatial prediction method uses only two neighboring pixels for
prediction, based on the angular projection idea borrowed from block-based
intra prediction in lossy coding. This paper explores a method which uses three
neighboring pixels for prediction according to a two-dimensional correlation
model, and the used neighbor pixels and prediction weights change depending on
intra mode. To find the best prediction weights for each intra mode, a
two-stage offline optimization algorithm is used and a number of implementation
aspects are discussed to simplify the proposed prediction method. The proposed
method is implemented in the HEVC reference software and experimental results
show that the explored 3-tap filtering method can achieve an average 11.34%
bitrate reduction over the default lossless intra coding in HEVC. The proposed
method also decreases average decoding time by 12.7% while it increases average
encoding time by 9.7%Comment: 10 pages, 7 figure
Fast intra prediction in the transform domain
In this paper, we present a fast intra prediction method based on separating the transformed coefficients. The
prediction block can be obtained from the transformed and quantized neighboring block generating minimum distortion
for each DC and AC coefficients independently. Two prediction methods are proposed, one is full block search
prediction (FBSP) and the other is edge based distance prediction (EBDP), that find the best matched transformed
coefficients on additional neighboring blocks. Experimental results show that the use of transform coefficients
greatly enhances the efficiency of intra prediction whilst keeping complexity low compared to H.264/AVC
A two-stage video coding framework with both self-adaptive redundant dictionary and adaptively orthonormalized DCT basis
In this work, we propose a two-stage video coding framework, as an extension
of our previous one-stage framework in [1]. The two-stage frameworks consists
two different dictionaries. Specifically, the first stage directly finds the
sparse representation of a block with a self-adaptive dictionary consisting of
all possible inter-prediction candidates by solving an L0-norm minimization
problem using an improved orthogonal matching pursuit with embedded
orthonormalization (eOMP) algorithm, and the second stage codes the residual
using DCT dictionary adaptively orthonormalized to the subspace spanned by the
first stage atoms. The transition of the first stage and the second stage is
determined based on both stages' quantization stepsizes and a threshold. We
further propose a complete context adaptive entropy coder to efficiently code
the locations and the coefficients of chosen first stage atoms. Simulation
results show that the proposed coder significantly improves the RD performance
over our previous one-stage coder. More importantly, the two-stage coder, using
a fixed block size and inter-prediction only, outperforms the H.264 coder
(x264) and is competitive with the HEVC reference coder (HM) over a large rate
range
- …