TY - JOUR
T1 - Hybrid All Zero Soft Quantized Block Detection for HEVC
AU - Cui, Jing
AU - Xiong, Ruiqin
AU - Zhang, Xinfeng
AU - Wang, Shiqi
AU - Wang, Shanshe
AU - Ma, Siwei
AU - Gao, Wen
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10
Y1 - 2018/10
N2 - Transform and quantization account for a considerable amount of computation time in video encoding process. However, there are a large number of discrete cosine transform coefficients which are finally quantized into zeros. In essence, blocks with all zero quantized coefficients do not transmit any information, but still occupy substantial unnecessary computational resources. As such, detecting all-zero block (AZB) before transform and quantization has been recognized to be an efficient approach to speed up the encoding process. Instead of considering the hard-decision quantization (HDQ) only, in this paper, we incorporate the properties of soft-decision quantization into the AZB detection. In particular, we categorize the AZB blocks into genuine AZBs (G-AZB) and pseudo AZBs (P-AZBs) to distinguish their origins. For G-AZBs directly generated from HDQ, the sum of absolute transformed difference-based approach is adopted for early termination. Regarding the classification of P-AZBs which are generated in the sense of rate-distortion optimization, the rate-distortion models established based on transform coefficients together with the adaptive searching of the maximum transform coefficient are jointly employed for the discrimination. Experimental results show that our algorithm can achieve up to 24.16% transform and quantization time-savings with less than 0.06% RD performance loss. The total encoder time saving is about 5.18% on average with the maximum value up to 9.12%. Moreover, the detection accuracy of larger TU sizes, such as 16 × 16 and 32 × 32 can reach to 95% on average.
AB - Transform and quantization account for a considerable amount of computation time in video encoding process. However, there are a large number of discrete cosine transform coefficients which are finally quantized into zeros. In essence, blocks with all zero quantized coefficients do not transmit any information, but still occupy substantial unnecessary computational resources. As such, detecting all-zero block (AZB) before transform and quantization has been recognized to be an efficient approach to speed up the encoding process. Instead of considering the hard-decision quantization (HDQ) only, in this paper, we incorporate the properties of soft-decision quantization into the AZB detection. In particular, we categorize the AZB blocks into genuine AZBs (G-AZB) and pseudo AZBs (P-AZBs) to distinguish their origins. For G-AZBs directly generated from HDQ, the sum of absolute transformed difference-based approach is adopted for early termination. Regarding the classification of P-AZBs which are generated in the sense of rate-distortion optimization, the rate-distortion models established based on transform coefficients together with the adaptive searching of the maximum transform coefficient are jointly employed for the discrimination. Experimental results show that our algorithm can achieve up to 24.16% transform and quantization time-savings with less than 0.06% RD performance loss. The total encoder time saving is about 5.18% on average with the maximum value up to 9.12%. Moreover, the detection accuracy of larger TU sizes, such as 16 × 16 and 32 × 32 can reach to 95% on average.
KW - all zero block (AZB) detection
KW - DCT
KW - rate-distortion modeling
KW - soft-decision quantization
UR - https://www.scopus.com/pages/publications/85047068413
U2 - 10.1109/TIP.2018.2837351
DO - 10.1109/TIP.2018.2837351
M3 - 文章
C2 - 29985138
AN - SCOPUS:85047068413
SN - 1057-7149
VL - 27
SP - 4987
EP - 5001
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
IS - 10
ER -