blob: 04d4181598c63b75ef532993852ffed4935d2b58 [file] [log] [blame]
#### 7.1 Underlying Theory of Coding {#h-07-01}
The basic idea used by the boolean coder is to consider the entire
data stream (either of the partitions in our case) as the binary
expansion of a single number x with 0 <= x < 1. The bits (or bytes)
in x are of course written from high to low order, and if b[j] (B[j])
is the j^(th) bit (byte) in the partition, the value x is simply the
sum (starting with j = 1) of pow(2, -j) * b[j] or pow(256, -j) *
Before the first bool is coded, all values of x are possible.
The coding of each bool restricts the possible values of x in
proportion to the probability of what is coded. If p1 is the
probability of the first bool being zero and a zero is coded, the
range of possible values of x is restricted to 0 <= x < p1. If a one
is coded, the range becomes p1 <= x < 1.
The coding continues by repeating the same idea. At every stage,
there is an interval a <= x < b of possible values of x. If p is the
probability of a zero being coded at this stage and a zero is coded,
the interval becomes a <= x < a + (p*(b-a)). If a one is coded, the
possible values of x are restricted to a + (p*(b-a)) <= x < b.
Assuming that only finitely many values are to be coded, after the
encoder has received the last bool, it can write as its output any
value x that lies in the final interval. VP8 simply writes the left
endpoint of the final interval. Consequently, the output it would
make if encoding were to stop at any time either increases or stays
the same as each bool is encoded.
Decoding parallels encoding. The decoder is presented with the
number x, which has only the initial restriction 0 <= x < 1. To
decode the first bool, the decoder is given the first probability p1.
If x < p1, a zero is decoded; if x >= p1, a one is decoded. In
either case, the new restriction on x -- that is, the interval of
possible values of x -- is remembered.
Decoding continues in exactly the same way: If a <= x < b is the
current interval and we are to decode a bool with zero-probability p,
we return a zero if a <= x < a + (p*(b-a)) and a one if a + (p*(b-a))
<= x < b. In either case, the new restriction is remembered in
preparation for decoding the next bool.
The process outlined above uses real numbers of infinite precision to
express the probabilities and ranges. It is true that, if one could
actualize this process and coded a large number of bools whose
supplied probabilities matched their value distributions, the
datarate achieved would approach the theoretical minimum as the
number of bools encoded increased.
Unfortunately, computers operate at finite precision, and an
approximation to the theoretically perfect process described above is
necessary. Such approximation increases the datarate but, at quite
moderate precision and for a wide variety of data sets, this increase
is negligible.
The only conceptual limitations are, first, that coder probabilities
must be expressed at finite precision and, second, that the decoder
be able to detect each individual modification to the value interval
via examination of a fixed amount of input. As a practical matter,
many of the implementation details stem from the fact that the coder
can function using only a small "window" to incrementally read or
write the arbitrarily precise number x.