The Taub Faculty of Computer Science Events and Talks

Natural videos, given in the RGB color space, are characterized by high correlations between the primary colors (R, G and B). To reduce this redundancy, most video compression algorithms, like MPEG, decorrelate the color components by transforming the input video from the highly correlated RGB components into less correlated space such as YIQ or YCbCr.

In this work, we propose a different approach, which utilizes the natural high inter-color correlation. We have developed algorithms for video coding that benefit from the correlation of the primary colors in both the spatial and the frequency (DCT) domains. Video stream is subdivided into 3D blocks of variable size according to the contents along the spatial and the temporal axes. In each block, one of the colors is chosen as a 'base color', using a minimum reconstruction error criterion. While the 'base color' is coded using conventional tools, the two remaining components are encoded as approximation polynomials of the base color.

Experimental results show that the proposed approach outperforms presently available methods. Our conclusion is that the high correlation between primary RGB colors could be helpful for video coding and that the new spatio-temporal approach to video compression is more efficient than conventional decorrelation-based techniques.

*MSc final paper under the supervision of Dr. Moshe Porat