Digital Signal Processing Reference
In-Depth Information
13.5 JPEG Extensions
The JPEG standard provides for several extensions, some of
which are summarized below.
Huffman coding is popular, and has no intellectual property
restrictions, but some variants of JPEG use an alternate coding
method known as arithmetic coding. Arithmetic coding is more
efficient, adapting to changes in the statistical estimates of the
input data stream and is subject to patent limitations.
Variable quantization is an enhancement to the quantization
procedure of DCT output. This enhancement can be used with
the DCTs in JPEG except for the baseline JPEG. The quantization
values can be redefined prior to the start of an image scan but
must not be changed once they are within a scan.
In this method, the quantization values are scaled at the start
of each 8
matching the scale factors used to the AC
coefficients stored in the compressed data. Quantization values
may then be located and changed as needed, which allows for
variable quantization based on the characteristics of an image.
The variable quantizer continually adjusts during decoding to
provide higher quality at the expense of increasing the size of the
JPEG file. Conversely, the maximum size of the resulting JPEG file
can be set by constant adaptive adjustments made by the variable
quantizer.
Another extension is selective refinement, which selects
a given region of an image for further enhancement. The reso-
lution of this region of the image is improved using three methods
of selective refinement: progressive, hierarchical and component.
Progressive selective refinement is used only in the progressive
modes to add more bit resolution of near zero and non-zero DCT
coefficients in the region of the image. Hierarchical selective
refinement is used in JPEG hierarchical coding mode, and
permits for a region of an image to be refined by the next
differential image in a defined hierarchical sequence. It allows
higher quality or resolution in a given region of the image.
Component selective refinement permits a region of a frame to
contain fewer colors than are originally defined.
Image tiling is an enhancement that divides a single image
into smaller sub-images, which allows for smaller memory
buffers, quicker access in both volatile and disk memory and the
storing and compression of very large images. There are three
types of tiling: simple, pyramidal, and composite.
Simple tiling divides an image into multiple fixed-size tiles. All
simple tiles are coded from top to bottom, left to right, and are
8 block
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