Abstract
Discrete cosine transform (DCT), quantization (Q), inverse quantization (IQ) and inverse DCT (IDCT) are the building blocks in video coding standards adopted by ITU-T and MEPG. Under these standards, a lot of computations are required to perform the DCT, Q, IQ and IDCT operations. With this concern, a novel statistical model based on Gaussian distribution is proposed to predict zero quantized DCT (ZQDCT) coefficients in order to reduce the computational complexity of video encoding. Compared with other predictive models in the literature, the proposed model can detect more ZQDCT coefficients. Simulation results demonstrate that the proposed statistical model is superior to others in terms of speeding up video encoders. Moreover, a hybrid model is derived based on the proposed statistical model and mathematical analysis of individual DCT coefficients to further improve the encoding efficiency. © 2006 Elsevier Ltd. All rights reserved.
Original language | English |
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Pages (from-to) | 922-933 |
Journal | Image and Vision Computing |
Volume | 25 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1 Jun 2007 |
Externally published | Yes |
Funding
The authors acknowledge the City University of Hong Kong Strategic Grant 7001697 for the financial support.
Keywords
- Discrete cosine transform (DCT)
- Quantization (Q)
- Video encoding
- Zero quantized DCT (ZQDCT) coefficients