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"walala" <[EMAIL PROTECTED]> writes: > Why people think I want to lie upon seeing my question? Oh, it's my problem > that I did not clearly present the background... Partly. Partly also you posed the question in a slightly troll-like way. :-) > Here is the story: in deblocking of block DCT coded JPEG images, it was > known that the DCTed coefficients are Laplacian distributed... But now I am > looking at low bit rate JPEG images, so there are someking of artifacts... > in order to reconstruct the original images... many algorithms have been > devised... one possibility is to make the image coefficients more Laplcian > like... These dudes appear to use the fact that the coefficients are Laplacian to a reasonable level of accuracy: http://bmrc.berkeley.edu/research/publications/1996/110/imdsp.ps http://citeseer.nj.nec.com/smoot96study.html So what makes you say your coefficients are not? Are you looking at the right coefficients? > So that came my question: how to make data more Laplican like...Please give > me some detailed explanation as I am not veteran in statistics... Well, what variations do you have available? Does your modification have to fit into JPEG? Or can it be seen as a completely separate step? Usually, if you want to convert a random variable with one distribution to another distribution you need to find a function that relates the two random variables. A first, naive, approach might be to use the histogram of the data you have to find a piece-wise linear function that rescales the data so that its histogram is Laplacian. This technique is sometimes used in image processing to make greyscale images have a uniform brightness distribution (see e.g. http://www.cs.tcd.ie/Fergal.Shevlin/courses/4d4/4BA10/PixelBrightnessTransformations.pdf ) Ciao, Peter K. -- Peter J. Kootsookos "I will ignore all ideas for new works [..], the invention of which has reached its limits and for whose improvement I see no further hope." - Julius Frontinus, c. AD 84
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