Systems and methods for efficient video-related data processing

1. A method for dequantization and inverse transformation of an image signal, said method comprising:

receiving a plurality of quantized coefficient levels (c) that define an image;

receiving a quantization parameter (QP);

determining a periodic mantissa portion depending on QP%P, wherein P defines the period of said mantissa portion;

determining an exponential portion depending on QP/P;

computing reconstructed transform coefficients ({tilde over (w)} α ) from said plurality of quantized coefficient levels (c α ), said periodic mantissa portion and said exponential portion;

performing an inverse transformation on said reconstructed transform coefficients ({tilde over (w)} α ) thereby yielding scaled samples ({tilde over (x)}′ α );

computing reconstructed samples, (x″ α ) by normalizing the scaled samples using a constant normalization factor (M).

2. The method of claim 1 wherein P=6 and M=6 and wherein said computing a reconstructed transform coefficient comprises using a formula equivalent to {tilde over (w)} α =[c α ·R (QP%P) ]<<QP/P, wherein R is a mantissa portion of a and said dequantization scaling factor, and said computing reconstructed samples comprises using a formula equivalent to x″ α =({tilde over (x)}′ α +(1<<(M−1)))>>M.

3. A method for dequantization and inverse transformation of an image signal, said method comprising:

receiving a plurality of quantized coefficient levels (c) that define an image;

receiving a quantization parameter (QP);

determining a periodic mantissa portion R QP%P , wherein R is a mantissa portion of a dequantization scaling factor and P defines the period of said mantissa portion;

determining an exponential portion depending on QP/P;

computing reconstructed transform coefficients ({tilde over (w)} α ) wherein

{tilde over (w)} α =└c α ·R (QP%P) ┘<<( QP/P );

performing an inverse transformation on said reconstructed transform coefficients ({tilde over (w)}) thereby yielding transformed samples ({tilde over (x)}′);

computing reconstructed samples, (x″) using a formula equivalent to x″ α =({tilde over (x)}′ α +(1<<(M−1)))>>M, wherein M is a constant normalization factor.

4. An apparatus for dequantization and inverse transformation of an image signal, said apparatus comprising:

a first receiver for receiving a plurality of quantized coefficient levels (c) that define an image;

a second receiver for receiving a quantization parameter (QP);

a first processor for determining a periodic mantissa portion depending on QP%P, wherein P defines the period of said mantissa portion;

a second processor for determining an exponential portion depending on QP/P;

a third processor for computing reconstructed transform coefficients ({tilde over (w)} α ) from said plurality of quantized coefficient levels (c α ), said periodic mantissa portion and said exponential portion;

a fourth processor for performing an inverse transformation on said reconstructed transform coefficients ({tilde over (w)} α ) thereby yielding scaled samples ({tilde over (x)}′ α );

a fifth processor for computing reconstructed samples, ({tilde over (x)}″ α ) by normalizing the scaled samples using a constant normalization factor (M).

5. A computer-readable medium encoded with computing-executable instructions for directing a computer to perform dequantization and inverse transformation of an image signal, said computer-executable instructions comprising:

receiving a plurality of quantized coefficient levels (c) that define an image;

receiving a plurality of quantized coefficient levels (c) that define an image;

receiving a quantization parameter (QP);

determining a periodic mantissa portion depending on QP%P, wherein P defines the period of said mantissa portion;

determining an exponential portion depending on QP/P;

computing reconstructed transform coefficients ({tilde over (w)} α ) from said plurality of quantized coefficient levels (c α ), said periodic mantissa portion and said exponential portion;

performing an inverse transformation on said reconstructed transform coefficients ({tilde over (w)} α ) thereby yielding scaled samples ({tilde over (x)}′ α );

computing reconstructed samples, ({tilde over (x)}″ α ) by normalizing the scaled samples using a constant normalization factor (M).