The distribution characteristic of three-dimensional wavelet coefficients of video data was ana ed,and a scalable video coding algorithm was subsequently addressed based on hybrid three-dimensional tree and human visual system (HVS) characteristics.First,the hybrid tree structure was adaptively determined according to the auto-correlation of low-pass and high-pass coefficients.It reduced obviously the number of ion bits locating significant wavelet coefficients when scanning and processing low-pass and high-pass coefficients in temporal dimension.Second,each wavelet coefficient was weighted in terms of HVS sensitivity to its corresponding subband.Significant coefficients thus tended to be coded with high priority and arranged at the front of bitstream,and the reconstructed video quality was improved at low and medium bitrates to a great extent.Experimental results in terms of peak signal-to-noise ratio (PSNR) verified the effectiveness of the proposed algorithm on several test videos with varying characteristics.0.65dB,1.75dB,and 1.77dB higher PSNR are gained than asymmetric 3-D orientation tree for Y,U,and V components,respectively.Moreover,0.23dB,2.11dB,and 1.72dB higher PSNR are reached than single temporal-spatial orientation tree separately for Y,U,and V components.Besides,better subjective quality is obtained through effectively attenuating ringing artifact.