To acquire the optimal coding mode of each macroblock, the H.264/AVC encoder exhaustively calculates the ratedistortion
cost for all available modes and chooses the minimum one as the best mode. Therefore, the mode decision
process is very computationally demanding. To reduce the computation complexity of the rate-distortion cost, in this
paper, we propose a novel rate estimation model for the mode decision in H.264/AVC. By modeling the transform
coefficients with Generalized Gaussian distributions (GGD), a direct relationship between the magnitude and the
information bits of the quantized transform coefficients is deduced. Based on this deduction, the weighted sum of
quantized transform coefficients is proposed as an efficient bit-rate estimator of the residual blocks. Extensive
experiments show that the proposed algorithm can save up to 30% of total encoding time with ignorable degradation in
coding performance for both inter- and intra-mode decision.
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