A novel quality scalable video coding algorithm based on pattern recognition was proposed in this paper. The self-organizing map (SOM) was used for scalable video coding. A coarse pattern library and two fine pattern libraries were designed for the base layer coding and the enhancement layer coding, respectively. Experimental results show that the peak signal to noise ratio (PSNR) improvement of reconstructed video images is 1.06dB when the compression ratio is 100:1.
Neighborhood algorithm is an important part of 3D SOM algorithm. We proposed three kinds of neighborhood shape and two kinds of neighborhood decay function for threedimensional self-organizing feature maps (3D SOM) algorithm and applied them to three-dimensional image compression coding. Experimental results show that the 3D orthogonal cross neighborhood shape and exponential function algorithm have better peak signal to noise ratio (PSNR) and subject quality than others.
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