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Add a missing matrix which was referenced by the text. This was calculated using a spreadshet from the other two matricies. |
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==Quantization in image compression==
The human eye is fairly good at seeing small differences in [[brightness]] over a relatively large area, but not so good at distinguishing the exact strength of a high frequency brightness variation. This fact allows one to get away with greatly reducing the amount of information in the high frequency components. This is done by simply dividing each component in the frequency ___domain by a constant for that component, and then rounding to the nearest integer. This is the main lossy operation in the whole process. As a result of this, it is typically the case that many of the higher frequency components are rounded to zero, and many of the rest become small positive or negative numbers.
This is an example DCT coefficient matrix: <!--NOTE: this matrix was generated using random numbers and the other two matricies. It may not actually work well with an iDCT. -->
:<math>
\begin{bmatrix}
-415 & -33 & -58 & 35 & 58 & -51 & -15 & -12 \\
5 & -34 & 49 & 18 & 27 & 1 & -5 & 3 \\
-46 & 14 & 80 & -35 & -50 & 19 & 7 & -18 \\
-53 & 21 & 34 & -20 & 2 & 34 & 36 & 12 \\
9 & -2 & 9 & -5 & -32 & -15 & 45 & 37 \\
-8 & 15 & -16 & 7 & -8 & 11 & 4 & 7 \\
19 & -28 & -2 & -26 & -2 & 7 & -44 & -21 \\
18 & 25 & -12 & -44 & 35 & 48 & -37 & -3
\end{bmatrix}
</math>
A common quantization matrix is: <!--FIXME: where does this matrix come from? afaict this is exactly the part that would change with encoder and quality setting so calling it common seems a bit of a stretch especially with no source [[User:Plugwash|Plugwash]] 12:30, 23 May 2005 (UTC)-->
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