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From: marinell@dalcs.UUCP (Kevin Marinelli)
Newsgroups: comp.graphics
Subject: Re: reverse dithering
Message-ID: <2715@dalcs.UUCP>
Date: Thu, 19-Nov-87 09:06:23 EST
Article-I.D.: dalcs.2715
Posted: Thu Nov 19 09:06:23 1987
Date-Received: Sun, 22-Nov-87 01:28:57 EST
References: <1525@ssc-vax.UUCP> <34159@sun.uucp> <4579@cit-vax.Caltech.Edu>
Reply-To: marinell@dalcs.UUCP (Kevin Marinelli)
Organization: Math, Stats & CS, Dalhousie University, Halifax, NS, Canada
Lines: 53
Keywords: dithering, halftone, gray scale

In article <4579@cit-vax.Caltech.Edu> flaig@cit-vlsi.UUCP (Charles M. Flaig) writes:
>In article <34159@sun.uucp> cmcmanis@sun.UUCP (Chuck McManis) writes:
>>In article <1525@ssc-vax.UUCP> dickey@ssc-vax.UUCP (Frederick J Dickey) writes:
>>>My question is the following: Given the image in the dithered form,
>>>is there any reasonable way of reconstructing the original gray scale
>>>image?
>>
>>If you know the region of the dither (like 4 X 4 squares or something) you
>>can just average all of the pixels in the region and multiply that by the 
>>a normalizing factor.
>>--Chuck McManis

  I have tried to do something similar myself recently, but by using
  grey levels only. I have used two techniques, both however have their 
  problems.

  It is assumed that the dithered image uses 1 bit per pixel, although
  this may be altered if necessary.

  Algorithm 1

	for each pixel in the image, the grey level = sum of the bits that
	are on for each of its neighbors, and itself. This gives a 9 level
	grey map. (this may be extended to neighbors within 2 pixels for 
	a 16 level grey map.

	This technique preserves the spacial resolution of the dithered
	image, but causes the grey level map to look "Blurred". In many
	cases this is not a problem. If there are a lot of high contrast
	edges, then the bluring is more pronounced. E.g for black text
	on a white background.

 Algorithm 2

	for every block of N X N bits, the grey level is the sum of the
	on bits. The next pixel in the sequence is the next adjacent 
	block of N X N bits.

	This technique compresses the spacial resolution of the dithered
	image to 1/N. Bluring of the image is much less of a problem. This
	works best for very large dithered images where the loss of spacial
	resolution is not important.

 I have used the above technique for converting images from an apple Mac
 for display on an IBM PGA card. Because the images on the Mac were
 monochromatic dithered images, it was not possible to restore any actual
 colour information to the image.


-- 
Kevin Marinelli
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