The two-dimensional discrete cosine transform (2-D DCT) and its subsequent quantization are widely used in standard video encoders. However, since most DCT coefficients become zeros after quantization, a number of redundant computations are performed. This paper proposes a hybrid statistical model used to predict the zeroquantized DCT (ZQDCT) coefficients for intratransform and to achieve better real-time performance. First, each pixel block at the input of DCT is decomposed into a series of mean values and a residual block. Subsequently, a statistical model based on Gaussian distribution is used to predict the ZQDCT coefficients of the residual block. Then, a sufficient condition under which each quantized coefficient becomes zero is derived from the mean values. Finally, a hybrid model to speed up the DCT and quantization calculations is proposed. Experimental results show that the proposed model can reduce more redundant computations and achieve better real-time performance than the reference in the literature at the cost of negligible video quality degradation. Experiments also show that the proposed model significantly reduces multiplications for DCT and quantization. This is particularly suitable for processors in portable devices where multiplications consume more power than additions. Computational reduction implies longer battery lifetime and energy economy.
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