Efficient Encoding of Colored Pictures in R, G, B Components

The encoding of colored pictures in components has attracted a lot of attention. In this paper, for their efficient transmission in the 2-3 bit/pel range, the direct encoding of the red ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</tex> ), green ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">G</tex> ), and blue ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</tex> ) primaries is investigated. Differential PCM with vector quantization is used and the encoding efficiencies are compared to the similar result obtained using the properly converted luminance ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Y</tex> ) and chrominance ( <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">I,Q</tex> ) component signals. A new quantization scheme is proposed for <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RGB</tex> encoding to improve the picture quality. As a result, it is shown that <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RGB</tex> encoding can attain a comparable or slightly higher encoding efficiency as compared to <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">YIQ</tex> encoding, and a higher resolution can be obtained for strong color edges defined by the primary colors, but the resulting picture quality is much noisier; thus, it is better suited for such applications in which the edges of primary colors play important roles, such as in graphics materials. An adaptive vector quantization is introduced in order to apply the proposed <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">RGB</tex> encoding scheme to a wider range of pictures. The quantity called activity is introduced, considering the form of the predictor used. The optimum adaptive scheme is derived and its effectiveness is verified through simulations.