Name
Abstract | ||
|---|---|---|
In this paper, an all-zero block detection scheme is proposed prior to DCT to reduce the encoding complexity for high efficiency video coding (HEVC). Since many coding blocks tend to have all zero coefficients after DCT and quantization, it is worthwhile to detect all-zero-quantized blocks for input residual blocks before DCT so that subsequent transform and quantization can be skipped. Unlike previous coding standards, HEVC adopts large transform sizes such as $16 \\times 16$ and $32 \\times 32$ in addition to $4 \\times 4$ and $8 \\times 8$. It becomes more difficult to accurately detect all-zero blocks in HEVC because the large transform blocks contains more variety of content characteristics than smaller ones, thus making it ineffective the existing all-zero block (AZB) detection schemes for large transform blocks in HEVC. In this paper, a novel AZB detection scheme is proposed for the case that Hadamard transform is used as a distortion metric for RDO in HEVC. Statistical upper bounds to be all-zero blocks are derived using the relationship between Walsh Hadamard and DCT transform kernels. Then, a small number of quantized coefficients in a upper left corner of a transform block, which are obtained using the relations between Hadamard transform and DCT, are examined for AZB detection. For $32 \\times 32$ blocks, DC coefficients of $8 \\times 8$ sub-blocks are further examined for AZB detection. The experimental results demonstrate that the proposed scheme detects 87.79% of actual AZBs with 2.87% false alarm rate in average, outperforming the state-of-the-art method. Computational complexity to detect AZB is almost negligible compared to the conventional method. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TMM.2016.2557075 | IEEE Trans. Multimedia |
Keywords | Field | DocType |
Discrete cosine transforms,Encoding,Kernel,Quantization (signal),Complexity theory,Upper bound | Upper and lower bounds,Computer science,Discrete cosine transform,Theoretical computer science,Artificial intelligence,Kernel (linear algebra),Pattern recognition,Algorithm,Encoder,Constant false alarm rate,Quantization (signal processing),Hadamard transform,Computational complexity theory | Journal |
Volume | Issue | ISSN |
18 | 7 | 1520-9210 |
Citations | PageRank | References |
7 | 0.61 | 17 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bumshik Lee | 1 | 193 | 12.40 |
| Jaehong Jung | 2 | 7 | 0.61 |
| Munchurl Kim | 3 | 858 | 68.28 |