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Diffstat (limited to 'pnmnlfilt.html')
| -rw-r--r-- | pnmnlfilt.html | 20 |
1 files changed, 10 insertions, 10 deletions
diff --git a/pnmnlfilt.html b/pnmnlfilt.html index e0cd124a..e2cf5aee 100644 --- a/pnmnlfilt.html +++ b/pnmnlfilt.html @@ -40,7 +40,7 @@ subject pixel (ie. there will be no filtering effect). A radius value of 1.0 means that the 7 hexagons essentially cover the 3x3 immediate neighbor square. -<p>Your choice of "alpha" parameter selects among the three +<p>Your choice of "alpha" parameter selects among the three modes. <H3 id="alphatrimmedmean"> @@ -51,17 +51,17 @@ the 7 hexagon values, but the 7 values are sorted by size and the top and bottom alpha portion of the 7 are excluded from the mean. This implies that an alpha value of 0.0 gives the same sort of output as a normal convolution (ie. averaging or smoothing filter), where radius -will determine the "strength" of the filter. A good value to +will determine the "strength" of the filter. A good value to start from for subtle filtering is alpha = 0.0, radius = 0.55 For a more blatant effect, try alpha 0.0 and radius 1.0 <P>An alpha value of 0.5 will cause the median value of the 7 hexagons to be used to replace the center pixel value. This sort of filter is -good for eliminating "pop" or single pixel noise from an +good for eliminating "pop" or single pixel noise from an image without spreading the noise out or smudging features on the image. Judicious use of the radius parameter will fine tune the filtering. Intermediate values of alpha give effects somewhere between -smoothing and "pop" noise reduction. For subtle filtering +smoothing and "pop" noise reduction. For subtle filtering try starting with values of alpha = 0.4, radius = 0.6 For a more blatant effect try alpha = 0.5, radius = 1.0 @@ -73,7 +73,7 @@ image. For each pixel the variance of the surrounding hexagon values is calculated, and the amount of smoothing is made inversely proportional to it. The idea is that if the variance is small then it is due to noise in the image, while if the variance is large, it is -because of "wanted" image features. As usual the radius +because of "wanted" image features. As usual the radius parameter controls the effective radius, but it probably advisable to leave the radius between 0.8 and 1.0 for the variance calculation to be meaningful. The alpha parameter sets the noise threshold, over @@ -121,16 +121,16 @@ CG&A May 1990 Page 23 by Mark E. Lee and Richard A. Redner, and has been enhanced to allow continuous alpha adjustment. <P>The optimal estimation filter is taken from an article -"Converting Dithered Images Back to Gray Scale" by Allen +"Converting Dithered Images Back to Gray Scale" by Allen Stenger, Dr Dobb's Journal, November 1992, and this article references -"Digital Image Enhancement and Noise Filtering by Use of Local -Statistics", Jong-Sen Lee, IEEE Transactions on Pattern Analysis +"Digital Image Enhancement and Noise Filtering by Use of Local +Statistics", Jong-Sen Lee, IEEE Transactions on Pattern Analysis and Machine Intelligence, March 1980. <P>The edge enhancement details are from <A HREF="pgmenhance.html">pgmenhance</A>, which is taken from Philip -R. Thompson's "xim" program, which in turn took it from -section 6 of "Digital Halftones by Dot Diffusion", +R. Thompson's "xim" program, which in turn took it from +section 6 of "Digital Halftones by Dot Diffusion", D. E. Knuth, ACM Transaction on Graphics Vol. 6, No. 4, October 1987, which in turn got it from two 1976 papers by J. F. Jarvis et. al. |