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doc/webp-*: fix some punctuation, grammar

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based on comments from:
https://datatracker.ietf.org/doc/draft-zern-webp/ballot/#draft-zern-webp_lars-eggert

Bug: webp:448
Change-Id: I0a410b28b7b62fb4552ea3db444743be61469fe8
This commit is contained in:
James Zern 2022-09-29 18:58:27 -07:00
parent 3ed2b27517
commit 8a6185dd27
2 changed files with 12 additions and 13 deletions
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2
doc/webp-container-spec.txt
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@ -25,7 +25,7 @@ to compress image data in a lossy way, or (ii) the WebP lossless encoding
(and possibly other encodings in the future). These encoding schemes should
make it more efficient than currently used formats. It is optimized for fast
image transfer over the network (e.g., for websites). The WebP format has
feature parity (color profile, metadata, animation etc) with other formats as
feature parity (color profile, metadata, animation, etc.) with other formats as
well. This document describes the structure of a WebP file.
The WebP container (i.e., RIFF container for WebP) allows feature support over

23
doc/webp-lossless-bitstream-spec.txt
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@ -51,7 +51,7 @@ the stream containing them, and bits of each byte are read in
least-significant-bit-first order. When multiple bits are read at the
same time, the integer is constructed from the original data in the
original order. The most significant bits of the returned integer are
also the most significant bits of the original data. Thus the statement
also the most significant bits of the original data. Thus, the statement
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
b = ReadBits(2);
@ -196,7 +196,7 @@ once. The transformations are used only for the main level ARGB image:
the subresolution images have no transforms, not even the 0 bit
indicating the end-of-transforms.
Typically an encoder would use these transforms to reduce the Shannon
Typically, an encoder would use these transforms to reduce the Shannon
entropy in the residual image. Also, the transform data can be decided
based on entropy minimization.
@ -568,7 +568,7 @@ distribution entropy coding of neighboring pixels, and gives some
arithmetic coding-like benefits to the entropy code, but it can only be
used when there are a small number of unique values.
`color_table_size` specifies how many pixels are combined together:
`color_table_size` specifies how many pixels are combined:
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
int width_bits;
@ -583,13 +583,12 @@ if (color_table_size <= 2) {
}
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
`width_bits` has a value of 0, 1, 2 or 3. A value of 0 indicates no
pixel bundling to be done for the image. A value of 1 indicates that two
pixels are combined together, and each pixel has a range of \[0..15\]. A
value of 2 indicates that four pixels are combined together, and each
pixel has a range of \[0..3\]. A value of 3 indicates that eight pixels
are combined together and each pixel has a range of \[0..1\], i.e., a
binary value.
`width_bits` has a value of 0, 1, 2 or 3. A value of 0 indicates no pixel
bundling to be done for the image. A value of 1 indicates that two pixels are
combined, and each pixel has a range of \[0..15\]. A value of 2 indicates that
four pixels are combined, and each pixel has a range of \[0..3\]. A value of 3
indicates that eight pixels are combined and each pixel has a range of \[0..1\],
i.e., a binary value.
The values are packed into the green component as follows:
@ -659,7 +658,7 @@ Each pixel is encoded using one of the three possible methods:
3. Color cache code: using a short multiplicative hash code (color cache
index) of a recently seen color.
The following sub-sections describe each of these in detail.
The following subsections describe each of these in detail.
#### 5.2.1 Prefix Coded Literals
@ -725,7 +724,7 @@ return offset + ReadBits(extra_bits) + 1;
{:#distance-mapping}
As noted previously, distance code is a number indicating the position of a
previously seen pixel, from which the pixels are to be copied. This sub-section
previously seen pixel, from which the pixels are to be copied. This subsection
defines the mapping between a distance code and the position of a previous
pixel.