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- From: pdh@netcom.com (Phil Howard )
- Subject: Re: best way to describe jpeg
- Message-ID: <1993Jan24.020112.9370@netcom.com>
- Organization: Netcom - Online Communication Services (408 241-9760 guest)
- References: <1993Jan15.2816.1029@dosgate>
- Distribution: comp
- Date: Sun, 24 Jan 1993 02:01:12 GMT
- Lines: 105
-
- "danny hawrysio" <danny.hawrysio@canrem.com> writes:
-
- > On a graphic BBS I'm often asked how JPEG works in technical terms (and
- >yet they want it a fashion they can understand), I find any
- >explanation I come with is too long and hard to understand for the
- >average computer graphics user. Has anybody come up with a brief but
- >yet all covering description of JPEG?
- > The JPEG frequent question list is really no help since they avoid the
- >questions by recommending periodicals.
-
-
- Since I am sort of in between with regard to understanding this compression,
- and because I frequently try to explain complicated things in simple terms,
- let me give this a try. I have read about JPEG from two sources, although
- I did not pay attention to the fine details needed to actually implement it
- (I might try my hand at that "someday").
-
- I assume the degree of technical terms most of the users on the graphic BBS
- Danny Hawrysio refers to are not wanting the specifications to implement
- JPEG, but just want to get an idea of what the technology is that is being
- employed. If implementation details are needed, the references usually
- provided on comp.compression.research and other places really are needed.
-
- Please do *NOT* distribute this until I have a chance to clean it up via
- feed back from others that REALLY know how JPEG works.
-
-
-
- A summary of JPEG
- by
- Philip D. Howard
-
-
- JPEG works with 24-bit color images. It functions separately in each of the
- 3 primary colors, that is, do the reds, then do the greens, then do the blues.
- The three colors are 8 bits each. It also works with gray scale 8-bit. The
- theory could also be applied in other ways.
-
- JPEG is not magic. It simply depends on the fact that certain spectral
- parts of the image (very tight repeating patterns in various angles) do
- not usually contribute much to the image as perceived by the human eye.
- Where such patterns really are present, they are noticeably significant
- and cover some area of the image.
-
- The image is chopped up into little squares of 8 pixels by 8 pixels in order
- to reduce the computation scale. These image segments are then analyzed by
- a method called the Digital Cosine Transform, which is similar in certain
- ways to a Fourier Transform. The result of this transform is that the various
- repetitious patterns are extracted with respect to their periodicy and their
- amplitude (the degree to which they contribute).
-
- The reason the DCT is done is because the non-noise part of most images will
- concentrate the information into a small portion of the DCT output. The DCT
- output has as many numbers of information as the original image, but because
- it is a spectral type of data (in 2 dimensions) the lower frequency groups
- are likely to hold most of the relevant information.
-
- The next step is to quantize the DCT output. The numbers have increments
- of 1 in their amplitudes when they come out of the DCT, but small changes
- in these values will typically not be visible except by the most analytical
- eye (or computer). The higher frequencies, which occur less, can suffer
- even greater amplitude changes before they get noticed. The quantization
- performed rounds the numbers to the lower multiple of a certain number.
- That number is different for different pieces of that DCT output.
-
- The quantization is the lossy step of JPEG. This lossyness typically reduces
- most of the higher frequency components to zero. This is what basically
- allows JPEG to store the image in a smaller space. The quantization is more
- severe when the loss level is set for greater loss. This results in more of
- the zeroes being produced.
-
- These quantized numbers are then formed into variable length integers that
- occupy only a few bits. The zeroes are treated as a special case since it
- is known that the quantizing results in a lot of them; they take the fewest
- bits, typically 1 bit and maybe fewer (I have not looked at this area of
- detail yet). The more loss there is, the more zeroes and the smaller the
- data. The non-zero numbers will also have less range and can be squeezed
- into few bits in many cases as well.
-
- The steps from DCT transform to outputting bits is done for each of the 3
- primary colors, and for each square the image is chopped into.
-
- The reverse simply involves converting the variable length numbers from
- their bits, and applying the reverse DCT transform. As before, this is
- done for each color and each block of the image until the whole image
- has been restored.
-
- JPEG performs somewhat poorly when working with images that have been a
- part of GIF files. The reason for this is that GIF also applies a form
- of information loss that is sufficiently different to come across as noise
- to the JPEG compression. What GIF does is force the full ranges of colors
- that JPEG could use (any pixel can be any of 16777216 colors) into a small
- subset of only 256 colors that can be chosen different for each image.
- While this distortion is visually small, it can make some difference in
- how small the image comes out in JPEG.
-
- The best way to compress a JPEG image is to start from the original 24-bit
- data. Images with less noise work better, of course, since noise can appear
- to be high frequency spectral components. Noise typically appears in the
- image as graininess.
- --
- /************************************************************************\
- | Phil Howard, pdh@netcom.com, KA9WGN Spell protection? "1(911)A1" |
- | "It's not broken... it's just functionally challenged" --Phil and Pete |
- \************************************************************************/
-