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- Xref: sparky comp.ai.neural-nets:4632 sci.image.processing:1439
- Newsgroups: comp.ai.neural-nets,sci.image.processing
- Path: sparky!uunet!zaphod.mps.ohio-state.edu!usc!rpi!sassoj
- From: sassoj@jec301.its.rpi.edu (John J. Sasso Jr.)
- Subject: RESPONSES TO IMAGE PROCESSING REFS
- Message-ID: <c5r20_b@rpi.edu>
- Nntp-Posting-Host: jec301.its.rpi.edu
- Organization: Rensselaer Polytechnic Institute, Troy NY
- Date: Mon, 21 Dec 1992 16:45:15 GMT
- Lines: 340
-
- From Tom.Lane@G.GP.CS.CMU.EDU Fri Dec 4 10:35:17 1992
- Date: Fri, 4 Dec 1992 10:32-EST
- From: Tom.Lane@G.GP.CS.CMU.EDU
- To: "John J. Sasso Jr." <sassoj@rpi.edu>
- Subject: Re: TEXTS ON IMAGE COMPRESSION?
-
- >including advanced techniques)? I am working with gray-scale images.
- >The images I work with generally have no sharp variation points (they look
- >as if they were low-pass filtered), so can anyone suggest a compression
-
- Assuming that you do not require lossless compression, JPEG would
- probably be a good bet. See the JPEG FAQ in comp.graphics or
- news.answers for software and references. Also read the
- comp.compression FAQ.
-
- regards, tom lane
-
-
- /********************************************************************************/
-
-
- From edsr!edsdrd!maa@uunet.UU.NET Fri Dec 4 13:38:14 1992
- Date: Fri, 4 Dec 92 13:25:21 EST
- From: edsr!edsdrd!maa@uunet.UU.NET (Matthew Maa)
- To: uunet!aix.rpi.edu!sassoj@uunet.UU.NET
- Subject: Re: TEXTS ON IMAGE COMPRESSION USING NNs?
-
- I don't think there is a book particularly devoted to the
- subject you are looking for. There are books covering
- NN applications to image compression. The following is
- the abstract of a paper I recently wrote. If it fits your
- need, I can email you the complete paper in postscript
- format.
-
- Matthew Maa, Ph.D.
- maa@edsdrd.eds.com
-
- --------------- Abstract start here ---------------------
-
- Neural Networks for Image Compression:
- A Survey
-
- Matthew Maa
-
- Electronic Data Systems
- Detroit Research and Development
-
-
- This paper surveys the neural network related methods being used for
- image compression. These methods can be categorized into two major
- groups, direct methods and vector quantization methods. Direct methods
- mostly adopt three-layered, feed-forward networks in which input and
- output layers have the same number of neurons and hidden layers have
- fewer neurons. These networks are trained via certain pre-selected
- learning schemes during the training stage so as to generate at output
- layers (approximately) the same images that were given to input layers.
- The first halves of these networks, from input layers to hidden layers,
- are encoders (compressors), while the second halves, from hidden layers
- to output layers, are decoders (decompressors). The outputs of neurons
- of hidden layers are considered compressed images since hidden layers
- have fewer neurons. For vector quantization methods, networks are used
- to generate a proper codebook of reference vectors, where a vector is a
- subimage. A subimage can then be encoded by using the index of its
- best-match reference vector in the codebook. Compression is achieved
- as a vector index having a shorter binary representation that the
- vector itself. Other related image compression methods, including
- fuzzy systems and iterated functions systems as implemented by neural
- networks, will also be addressed. All methods surveyed in this report
- are lossy, that is, they only render from compressed files an approxi-
- mate image to the original.
-
-
- /********************************************************************************/
-
- From manduca@mayo.EDU Fri Dec 4 16:04:27 1992
- Date: Fri, 4 Dec 92 15:04:12 CST
- From: manduca@mayo.EDU (Armando Manduca)
- To: sassoj@rpi.edu
- Subject: image compression text
-
-
- John -
-
- A book I liked very much is "Digital Image Compression
- Techniques" by M. Rabbani and P. Jones. It's put out by
- SPIE Press and is their tutorial text TT7. It's very
- well-written and thorough, starts out basic, and goes
- thru fairly advanced.
-
- --------------------------------------------------------------
- Armando Manduca Internet: manduca@mayo.edu
- Dept. of Physiology and Biophysics
- Mayo Foundation talk: (507)-284-8163
- Rochester, MN 55905 FAX: (507)-284-1632
- --------------------------------------------------------------
-
- /********************************************************************************/
-
- From paul@ais.org Fri Dec 4 18:44:32 1992
- Date: Fri, 4 Dec 92 18:44 EST
- From: paul@ais.org (Paul Vargo)
- To: sassoj@rpi.edu
- Subject: Re: TEXTS ON IMAGE COMPRESSION?
- Newsgroups: sci.image.processing
- Organization: UMCC
- Cc:
-
- Try "Practical Image Processing In C" written by........whoops
- forgot the name. It's published by John Wiley And Sons, Inc.
- 605 Third Ave. New York, N.Y. 10158-0012
-
- It covers the basics and a lil' on the advance techniques.
- A very good book IMO. Oh...Craig A. Lindley wrote it....
- and he also works for Hewlett Packard. So you may even
- be able to reach him via e-mail.
-
- I pretty proud of myself! :) I can't believe I remembered all
- that stuff....I'm usually poor at it. :)
-
- That's a start for ya.
-
- --
- |================================================|========================|
- | Paul J. Vargo, II paul@umcc.ais.org | "Love is a many |
- | AC Rochester Engineering & Research Center, GM | splintered thing" A.E. |
- |================================================|========================|
-
- /********************************************************************************/
-
- From provine@enel.ucalgary.ca Sat Dec 5 17:19:55 1992
- Date: Sat, 5 Dec 92 15:19:42 MST
- From: provine@enel.ucalgary.ca (Joseph Provine)
- To: sassoj@rpi.edu
- Subject: Re: TEXTS ON IMAGE COMPRESSION?
- Newsgroups: sci.image.processing
- Organization: ECE Department, U. of Calgary, Calgary, Alberta, Canada
- Cc:
-
- Hi!
- Digital coding of waveforms
- by Jayant and Noll
-
- Digital Pictures
- by Netravali and Haskell
-
- Digital Image Processing
- W. Pratt
-
- Some texts are included in comp.compression-faq
-
- I recently came across a book that includes recent developments as well:
-
- Digital Image Compression
- by Rabbani and Jones
-
- SPIE's selected papers on Image Coding.
-
- The new version of Gonzalez and Woods book (Digital Image Processing)
- includes a better chapter on Image Coding compared to the previous version.
-
- This is pretty much the popular (at least that is what I think) stuff.
-
- Now about Entropy coding:
- You can refer to Review papers on Image Compression by Jain (Proc. IEEE,
- Mar. 1981, pp:349-389), Netravali and Limb (Proc. IEEE, Mar 1980, pp366-406).
-
- The specific papers are:
- Huffman's paper (Proc. I.R.E, Sep. 1952, pp. 1098-1101)
- Arithmetic Coding:
- Rissanen and Langdon (IBM J. Res. develop. Mar. 1979, pp. 149-162)
- Witten, Neal and Cleary (Commn. of ACM, June 1987, pp. 520-540)
-
- Also Welch's paper on LZW coding gives brief account of the above
- techniques too(IEEE Computer, June 1984, pp. 8-19).
-
- Hope this helps you...
- Good Luck.
- provine@enel.ucalgary.ca
-
- /********************************************************************************/
-
- From hcbarth@afterlife.ncsc.mil Sat Dec 5 22:38:17 1992
- Date: Sat, 5 Dec 92 22:38:07 EST
- From: hcbarth@afterlife.ncsc.mil (Bart Bartholomew)
- To: sassoj@rpi.edu
- Subject: Re: TEXTS ON IMAGE COMPRESSION USING NNs?
- Newsgroups: comp.ai.neural-nets
- Organization: The Great Beyond
- Cc:
-
- John, there was apparently a paper on
- the topic of image compression using NNs presented at the
- recently completed IJCNN conference in Peiking. A summary
- of the conference was published a week or so back.
- BartB
-
- --
- "I'll need a sample." "Come again?" "No, once is enough." -Joel to Holling
- If there's one thing I just can't stand, it's intolerance.
- *No One* is responsible for my views, I'm a committee. Please do not
- infer that which I do not imply. hcbarth@afterlife.ncsc.mil
-
- /********************************************************************************/
-
- From paik@mlo.dec.com Mon Dec 7 15:47:12 1992
- Date: Mon, 7 Dec 92 15:55:29 -0500
- From: paik@mlo.dec.com (Samuel S. Paik)
- To: sassoj@rpi.edu
- Subject: Re: TEXTS ON IMAGE COMPRESSION?
- Newsgroups: sci.image.processing
- Organization: Digital Workstations Software Group
- Cc:
-
- In article <jp+2ma@rpi.edu> you write:
- > Can anyone refer me to any texts on image compression/coding (possibly
- >including advanced techniques)? I am working with gray-scale images.
- >The images I work with generally have no sharp variation points (they look
- >as if they were low-pass filtered), so can anyone suggest a compression
- >scheme which is best for compressing such images? Also, what is entropy
- >coding, and how is its performance? Furthermore, any references to research
- >articles on advanced image compression techniques would be greatly
- >appreciated.
- >
- > John
-
- I'd suggest you take a look at the comp.compression FAQ and the
- JPEG FAQ sheet (also found in comp.compression).
-
- As an intro text, I'd recommend "Digital Coding of Waveforms", N.S.
- Jayant and Peter Noll, Prentice-Hall, 1984. (This is real hard to find
- in a book store, but you might have luck in a good engineering
- library).
-
- A source for the latest in image compression is the ICASSP proceedings,
- the "International Conference on Audio, Speech, and Signal Processing".
- This is a mammoth conference (I think the last few years they've
- had over 5000 pages each year), and you'll have to wade through a lot.
- Much of it won't be understandable without a background however.
-
- You can get a nice freely-available and distributable JPEG codec
- via ftp. Try looking on ftp.uu.net in the graphics directory.
-
- Entropy coding maps from symbols to bits based on a probability model
- of the source s.t. the number of bits produced is minimized. Assuming
- you have a good model of your source, an optimal entropy coding (such
- as arithmetic coding) will produce the best compression on the
- average. (The catch, of course, is getting a good model of your
- source).
-
- Sam Paik
-
- p.s. Sorry, if this seems a bit nebulous, but my job has very little
- to do with image compression, so all my refs are at home.
-
- /********************************************************************************/
-
- From more@ee.oulu.fi Tue Dec 8 03:55:13 1992
- Date: Tue, 8 Dec 92 10:55:03 +0200
- From: Jyrki Alakuijala <more@ee.oulu.fi>
- To: sassoj@rpi.edu (John J. Sasso Jr.)
- Subject: TEXTS ON IMAGE COMPRESSION?
- Reply-To: more@stekt.oulu.fi
-
- If you have printed text, try convolution of your
- font set. This should be possible to implement by using FFT.
-
- I would try to code hand written text with some primary elements such as
- arcs and lines and so on... I don't know if it's a good method.
-
- Then you have all the standard image compression methods, of course.
-
- You might want to get rid of the low pass effect by some non-linear
- filter...
-
- You should scan through you librarys IEEE magazines... atleast on the
- last issue of IEEE medical imaging, there was a nice compression
- method based on linear prediction...
-
- Why don't you just treshold the images and compress the binary image? :-)
-
- --Jyrki Alakuijala
-
- /********************************************************************************/
-
- From slfjd@venus.ee.usu.edu Wed Dec 9 17:10:35 1992
- Date: Wed, 9 Dec 92 15:10:54 MST
- From: slfjd@venus.ee.usu.edu (sane sachin arvind)
- To: sassoj@rpi.edu (John J. Sasso Jr.)
- Subject: Re: TEXTS ON IMAGE COMPRESSION?
-
-
- It would be nice to try Vector Qyuantization on these type
- of images. I am also working in this area and VQ gives certainly
- very good results.
- If you want to try ready made programs go for JPEG. It's based
- transform coding.
- The book "Fundamentals of Digital Image Processing" By A.K. Jain
- chapter12 might give to basic idea of image compression. You may
- need to read basics from previous chapters. I have written code to
- do image compression using VQ. If you want I can send you the code.
-
- Best Luck!
-
- - Sachin Sane
-
-
- /********************************************************************************/
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